RevPartners.io is a consulting firm specializing in Revenue Operations (RevOps) that focuses on supporting B2B SaaS companies in accelerating their growth. With a wealth of expertise in revenue operations, RevPartners.io offers a diverse range of services tailored to meet the specific needs ...

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She worked in RevOps for different companies before founding Activate the Magic, giving her a ton of valuable experience, and now specializes in utilizing Salesforce to help leaders solve challenges in startups and growth companies.

31 RevOps Leaders to Follow to Maximize Your Profit

RevOps is rapidly growing among global companies. Here is the ultimate list of 2024 RevOps Salesforce statistics you need to know.

The Ultimate List of RevOps Salesforce Statistics for 2024 | Sonar

Find the best Revenue Operations Services Providers using real-time, up-to-date data from verified user reviews. Read unbiased insights, compare features &amp; see pricing for 12 solutions. Request demos &amp; free trials to discover the right product for your business.

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Revenue operations aligns the revenue functions within an org, allowing you to maintain revenue growth in a growth-stage SaaS company.

RevOps is crucial for growing SaaS companies

Strategy and execution of critical sales and marketing ops projects so early-stage companies can scale faster with the right resources at a lower cost.

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How can aligning teams and implementing revenue operations (RevOps) help companies achieve and exceed revenue goals? Find out from this latest study.

56% Companies Implementing RevOps and Team Alignment Confident ...

The definition of Revenue Operations is the convergence of marketing, sales and customer service into a unified strategy and organization. RevOps has been picking up speed among B2B companies, as leaders look to it as a solution to siloed inefficiencies and as a way to boost productivity and growth.

Revenue Operations: The Ultimate Guide to RevOps Benchmarks

Join Adam Ballai and Dan Veres from RevOps: CPQ, Approvals, and Deal Desk and Dan Libby from DealDeskReady for this special discussion on all things Deal Desk. This webinar is for you if you&#x27;re curious about: 🚦 What signs to look for that indicate your company might need a Deal Desk?

RevOps: CPQ, Approvals, and Deal Desk | LinkedIn

RevOps is the modern Deal Desk platform with a simple mission: enable businesses to build a scalable Deal Desk operation that helps their sales organizations close more deals faster, unify branding, reduce contract errors, and provide a centralized agreement repository.

RevOps | CPQ + Modern Deal Desk Platform

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This is the fourth and final part of a series of articles on how GenAI is revolutionizing Rev-Ops functions in enterprise technology businesses. In the first part, we saw some broad applications of Gen AI in Rev Ops. In the next two parts, we explored how GenAI use cases are being  deployed in Business Strategy and Planning, followed by its applications in Marketing. In this final part, we conclude by taking a look at how Gen AI is shaping the future of Customer Success. A little bit about myself - I am a Sr. Director of Growth and Rev Ops at Cisco. Here is my LinkedIn profile - prior to Cisco, I was a Manager at McKinsey, with a background in Industrial Robotics and Electrical Engineering. Enhancing Personalization:  Generative AI enables businesses to deliver highly personalized experiences by analyzing vast and different datasets to understand individual customer preferences and behaviors. This capability allows for tailored interactions with products, recommendations, and content curation that resonate with each customer, significantly improving their experience. Curated AI playlists from Spotify is just the tip of the iceberg - this capability is poised to revolutionize enterprise user landscape as well.
Improved Customer Support: AI-powered chatbots and virtual assistants can provide instant, 24/7 support, addressing common queries and troubleshooting issues in real-time in a highly personalized manner leveraging input and data from multiple sources. These tools have the potential to enhance the customer support experience by offering quick and accurate responses, reducing wait times, and improving overall satisfaction and adoption. Admittedly, this can also be a double edged sword - with the premium and desire for human interaction going up in parallel- but there is no doubt that a lot of the simple support tasks could be delivered via agents in most situations, helping human agents to be more productive and successful.
More accurate churn prediction and prevention: Generative AI can combine disparate vast datasets and identify nuanced insights around customer sentiment, enhancing its predictive analytics capabilities to identify patterns indicative of potential churn. By analyzing customer interactions and behaviors across different channels, AI can predict which customers are at risk of leaving and enable preemptive actions to retain them. This proactive approach helps in maintaining a loyal customer base. This also allows businesses to get better insights into customer’s usage of products, and derive input for further product and service enhancement.
Automating Repetitive Tasks: Language capabilities is where Generative AI shines the most - with the ability to handle repetitive tasks such as call notes, meeting minutes, and documentation, freeing up customer success managers (CSMs) to focus on more strategic activities. This automation increases efficiency and productivity of  CSMs — allowing them to focus on higher value activities.
Better Fraud Detection: While enhancing customer experience and success is a key business imperative, identifying fraudulent behavior is also equally important. By continuously learning and adapting based on customer interactions, Gen AI can help flag fraudulent behavior early and at scale, helping businesses identify and mitigate fraudulent activities, ensuring a secure and trustworthy environment for customers and partners. Generative AI is rapidly reshaping customer success and adoption by enhancing personalization, enhancing human productivity through automation and support from generative agents, and enabling data-driven decision-making at scale in a variety of use cases and circumstances. However, it is essential to ensure ethical use and maintain data integrity to fully capitalize on AI's potential in Customer Success as well as Rev Ops more broadly. While this article concludes this series, I look forward to observing and studying the innovations in this space in the coming days - the promises are strong and substantial, with the potential to change the function dramatically. This is the fourth and final part of a series of articles on how GenAI is revolutionizing Rev-Ops functions in enterprise technology businesses. In the first part , we saw some broad applications of Gen AI in Rev Ops. In the next two parts, we explored how GenAI use cases are being  deployed in Business Strategy and Planning , followed by its applications in Marketing . In this final part, we conclude by taking a look at how Gen AI is shaping the future of Customer Success. In the first part In the first part Business Strategy and Planning Marketing A little bit about myself - I am a Sr. Director of Growth and Rev Ops at Cisco. Here is my LinkedIn profile - prior to Cisco, I was a Manager at McKinsey, with a background in Industrial Robotics and Electrical Engineering. LinkedIn profile LinkedIn profile Enhancing Personalization:  Generative AI enables businesses to deliver highly personalized experiences by analyzing vast and different datasets to understand individual customer preferences and behaviors. This capability allows for tailored interactions with products, recommendations, and content curation that resonate with each customer, significantly improving their experience. Curated AI playlists from Spotify is just the tip of the iceberg - this capability is poised to revolutionize enterprise user landscape as well. Improved Customer Support: AI-powered chatbots and virtual assistants can provide instant, 24/7 support, addressing common queries and troubleshooting issues in real-time in a highly personalized manner leveraging input and data from multiple sources. These tools have the potential to enhance the customer support experience by offering quick and accurate responses, reducing wait times, and improving overall satisfaction and adoption. Admittedly, this can also be a double edged sword - with the premium and desire for human interaction going up in parallel- but there is no doubt that a lot of the simple support tasks could be delivered via agents in most situations, helping human agents to be more productive and successful. More accurate churn prediction and prevention: Generative AI can combine disparate vast datasets and identify nuanced insights around customer sentiment, enhancing its predictive analytics capabilities to identify patterns indicative of potential churn. By analyzing customer interactions and behaviors across different channels, AI can predict which customers are at risk of leaving and enable preemptive actions to retain them. This proactive approach helps in maintaining a loyal customer base. This also allows businesses to get better insights into customer’s usage of products, and derive input for further product and service enhancement. Automating Repetitive Tasks: Language capabilities is where Generative AI shines the most - with the ability to handle repetitive tasks such as call notes, meeting minutes, and documentation, freeing up customer success managers (CSMs) to focus on more strategic activities. This automation increases efficiency and productivity of  CSMs — allowing them to focus on higher value activities. Better Fraud Detection: While enhancing customer experience and success is a key business imperative, identifying fraudulent behavior is also equally important. By continuously learning and adapting based on customer interactions, Gen AI can help flag fraudulent behavior early and at scale, helping businesses identify and mitigate fraudulent activities, ensuring a secure and trustworthy environment for customers and partners. Enhancing Personalization:  Generative AI enables businesses to deliver highly personalized experiences by analyzing vast and different datasets to understand individual customer preferences and behaviors. This capability allows for tailored interactions with products, recommendations, and content curation that resonate with each customer, significantly improving their experience. Curated AI playlists from Spotify is just the tip of the iceberg - this capability is poised to revolutionize enterprise user landscape as well . Curated AI playlists from Spotify is just the tip of the iceberg Curated AI playlists from Spotify is just the tip of the iceberg revolutionize enterprise user landscape as well revolutionize enterprise user landscape as well Improved Customer Support: AI-powered chatbots and virtual assistants can provide instant, 24/7 support, addressing common queries and troubleshooting issues in real-time in a highly personalized manner leveraging input and data from multiple sources. These tools have the potential to enhance the customer support experience by offering quick and accurate responses, reducing wait times, and improving overall satisfaction and adoption. Admittedly, this can also be a double edged sword - with the premium and desire for human interaction going up in parallel- but there is no doubt that a lot of the simple support tasks could be delivered via agents in most situations, helping human agents to be more productive and successful. AI-powered chatbots and virtual assistants AI-powered chatbots and virtual assistants More accurate churn prediction and prevention: Generative AI can combine disparate vast datasets and identify nuanced insights around customer sentiment, enhancing its predictive analytics capabilities to identify patterns indicative of potential churn . By analyzing customer interactions and behaviors across different channels, AI can predict which customers are at risk of leaving and enable preemptive actions to retain them. This proactive approach helps in maintaining a loyal customer base. This also allows businesses to get better insights into customer’s usage of products, and derive input for further product and service enhancement. patterns indicative of potential churn Automating Repetitive Tasks: Language capabilities is where Generative AI shines the most - with the ability to handle repetitive tasks such as call notes, meeting minutes, and documentation, freeing up customer success managers (CSMs) to focus on more strategic activities. This automation increases efficiency and productivity of  CSMs — allowing them to focus on higher value activities. increases efficiency and productivity of  CSMs Better Fraud Detection: While enhancing customer experience and success is a key business imperative, identifying fraudulent behavior is also equally important. By continuously learning and adapting based on customer interactions, Gen AI can help flag fraudulent behavior early and at scale , helping businesses identify and mitigate fraudulent activities, ensuring a secure and trustworthy environment for customers and partners. Gen AI can help flag fraudulent behavior early and at scale Gen AI can help flag fraudulent behavior early and at scale Generative AI is rapidly reshaping customer success and adoption by enhancing personalization, enhancing human productivity through automation and support from generative agents, and enabling data-driven decision-making at scale in a variety of use cases and circumstances. However, it is essential to ensure ethical use and maintain data integrity to fully capitalize on AI's potential in Customer Success as well as Rev Ops more broadly. While this article concludes this series, I look forward to observing and studying the innovations in this space in the coming days - the promises are strong and substantial, with the potential to change the function dramatically.

Reimagining Rev-Ops with Gen AI: Customer Success

This is the third part of a series of articles on how GenAI is revolutionizing Rev-Ops functions in enterprise technology businesses. In the first part, we saw some broad applications of Gen AI in Rev Ops. In the second article, we explored how GenAI use cases are being developed and deployed in the first of the four core Rev Ops pillars - business strategy and planning. In this article, we move on to the second Rev Ops pillar- Marketing. A little bit about myself - I am a Sr. Director of Rev Ops at Cisco. Here is my LinkedIn profile - prior to Cisco, I was a Manager at McKinsey, with a background in Industrial Robotics and Electrical Engineering. Marketing is one of the principal functional areas that is primed to leverage the full potential of generative technology : multi-modality (text, audio,and video), scale, rapid iteration, automation, and creativity- all can be leveraged to unlock a step-change in how Marketing is executed. And Enterprises big and small are already leveraging these capabilities in their day-to-day. Key advantages of Gen AI in marketing: Enhanced customer understanding at scale: GenAI based capabilities help generate  deeper insights into customer preferences and persona, from a variety of structured and unstructured data including video interactions, customer feedback, product / service usage, and telemetrics to generate a truly 360 degree view of customers and leads, improving conversion rates and quality of engagement. Systems are already capable of taking this a bit further, generating product recommendations, as shown by Stitch Fix.


Hyper Personalization at scale: Previously, marketing efforts had to be prioritized to the biggest customer opportunities, and the best that B2B sales came to personalized marketing was Account Based Marketing. Gen AI offers the ability to deliver unprecedented levels of personalization of campaigns and strategies at scale. Marketers can now go beyond audience segments and be truly personalized even in lower tiers like SMB which previously were starved of quality marketing resourcing.


Content creation and automation : Gen AI is multi-modal, and can be extremely creative, reducing time and resources required to create individualized marketing campaigns, collateral, landing pages, and email campaigns. What previously took weeks, can now be accomplished in hours with a fraction of the manpower needed. Companies that are leveraging AI to generate extremely personalized email campaigns have already started seeing differentiated results.


Marketing Analytics and Strategy: Gen AI has unprecedented ability to combine vast and disparate data sets to generate reliable and nuanced insights faster. It enhances the accuracy of key tools of marketers such as attribution mix modeling, media mix optimization, and Search Engine Optimization, while lowering marginal cost dramatically. It also facilitates rapid experimentation and A/B testing, and optimization of campaigns across multiple dimensions. One no longer needs an army of analysts to support a growth campaign- just the right combination of skills and tools.


Automation and efficiency: McKinsey estimates that gen AI could increase marketing productivity by 5-15%, worth about $463 billion annually. The productivity enhancement is expected to happen across three dimensions: human augmentation (providing leverage to human teams, helping them scale), automated agents working alongside humans to accomplish complex tasks, and eventually, through the creation of automated teams that own significant portions of workflows. What sounded like distant future is almost here today - and the race is on to be the first and best at leveraging the potential of this technology to the fullest extent. As the Gen AI landscape and capabilities evolve, adoption is expanding and new workflows and applications of Gen AI in Marketing are being uncovered rapidly. The rich entrepreneurial activity in this space is testament to the value at stake. But as the industry collectively navigates this space, it will be important to do so with adequate guardrails around privacy, and content rights - two of the most important concerns with the evolution of Gen AI. And these concerns are extremely valid and noteworthy in this space. It will be interesting to watch how industry, advocate groups and governments come together to shape this space in the coming days. This is the third part of a series of articles on how GenAI is revolutionizing Rev-Ops functions in enterprise technology businesses. In the first part , we saw some broad applications of Gen AI in Rev Ops. In the second article, we explored how GenAI use cases are being developed and deployed in the first of the four core Rev Ops pillars - business strategy and planning. In this article, we move on to the second Rev Ops pillar- Marketing. In the first part In the first part A little bit about myself - I am a Sr. Director of Rev Ops at Cisco. Here is my LinkedIn profile - prior to Cisco, I was a Manager at McKinsey, with a background in Industrial Robotics and Electrical Engineering. LinkedIn profile LinkedIn profile Marketing is one of the principal functional areas that is primed to leverage the full potential of generative technology : multi-modality (text, audio,and video), scale, rapid iteration, automation, and creativity- all can be leveraged to unlock a step-change in how Marketing is executed. And Enterprises big and small are already leveraging these capabilities in their day-to-day. Key advantages of Gen AI in marketing: Enhanced customer understanding at scale: GenAI based capabilities help generate  deeper insights into customer preferences and persona, from a variety of structured and unstructured data including video interactions, customer feedback, product / service usage, and telemetrics to generate a truly 360 degree view of customers and leads, improving conversion rates and quality of engagement. Systems are already capable of taking this a bit further, generating product recommendations, as shown by Stitch Fix. Hyper Personalization at scale: Previously, marketing efforts had to be prioritized to the biggest customer opportunities, and the best that B2B sales came to personalized marketing was Account Based Marketing. Gen AI offers the ability to deliver unprecedented levels of personalization of campaigns and strategies at scale. Marketers can now go beyond audience segments and be truly personalized even in lower tiers like SMB which previously were starved of quality marketing resourcing. Content creation and automation : Gen AI is multi-modal, and can be extremely creative, reducing time and resources required to create individualized marketing campaigns, collateral, landing pages, and email campaigns. What previously took weeks, can now be accomplished in hours with a fraction of the manpower needed. Companies that are leveraging AI to generate extremely personalized email campaigns have already started seeing differentiated results. Marketing Analytics and Strategy: Gen AI has unprecedented ability to combine vast and disparate data sets to generate reliable and nuanced insights faster. It enhances the accuracy of key tools of marketers such as attribution mix modeling, media mix optimization, and Search Engine Optimization, while lowering marginal cost dramatically. It also facilitates rapid experimentation and A/B testing, and optimization of campaigns across multiple dimensions. One no longer needs an army of analysts to support a growth campaign- just the right combination of skills and tools. Automation and efficiency: McKinsey estimates that gen AI could increase marketing productivity by 5-15%, worth about $463 billion annually. The productivity enhancement is expected to happen across three dimensions: human augmentation (providing leverage to human teams, helping them scale), automated agents working alongside humans to accomplish complex tasks, and eventually, through the creation of automated teams that own significant portions of workflows. What sounded like distant future is almost here today - and the race is on to be the first and best at leveraging the potential of this technology to the fullest extent. Enhanced customer understanding at scale: GenAI based capabilities help generate  deeper insights into customer preferences and persona, from a variety of structured and unstructured data including video interactions, customer feedback, product / service usage, and telemetrics to generate a truly 360 degree view of customers and leads, improving conversion rates and quality of engagement. Systems are already capable of taking this a bit further, generating product recommendations, as shown by Stitch Fix. Enhanced customer understanding at scale: GenAI based capabilities help generate  deeper insights into customer preferences and persona, from a variety of structured and unstructured data including video interactions, customer feedback, product / service usage, and telemetrics to generate a truly 360 degree view of customers and leads, improving conversion rates and quality of engagement. Systems are already capable of taking this a bit further, generating product recommendations, as shown by Stitch Fix. help generate  deeper insights help generate  deeper insights Hyper Personalization at scale: Previously, marketing efforts had to be prioritized to the biggest customer opportunities, and the best that B2B sales came to personalized marketing was Account Based Marketing. Gen AI offers the ability to deliver unprecedented levels of personalization of campaigns and strategies at scale. Marketers can now go beyond audience segments and be truly personalized even in lower tiers like SMB which previously were starved of quality marketing resourcing. Hyper Personalization at scale: Previously, marketing efforts had to be prioritized to the biggest customer opportunities, and the best that B2B sales came to personalized marketing was Account Based Marketing. Gen AI offers the ability to deliver unprecedented levels of personalization of campaigns and strategies at scale . Marketers can now go beyond audience segments and be truly personalized even in lower tiers like SMB which previously were starved of quality marketing resourcing. the ability to deliver unprecedented levels of personalization of campaigns and strategies at scale the ability to deliver unprecedented levels of personalization of campaigns and strategies at scale Content creation and automation : Gen AI is multi-modal, and can be extremely creative, reducing time and resources required to create individualized marketing campaigns, collateral, landing pages, and email campaigns. What previously took weeks, can now be accomplished in hours with a fraction of the manpower needed. Companies that are leveraging AI to generate extremely personalized email campaigns have already started seeing differentiated results. Content creation and automation : Gen AI is multi-modal, and can be extremely creative, reducing time and resources required to create individualized marketing campaigns, collateral, landing pages, and email campaigns. What previously took weeks, can now be accomplished in hours with a fraction of the manpower needed. Companies that are leveraging AI to generate extremely personalized email campaigns have already started seeing differentiated results . email campaigns have already started seeing differentiated results email campaigns have already started seeing differentiated results Marketing Analytics and Strategy: Gen AI has unprecedented ability to combine vast and disparate data sets to generate reliable and nuanced insights faster. It enhances the accuracy of key tools of marketers such as attribution mix modeling, media mix optimization, and Search Engine Optimization, while lowering marginal cost dramatically. It also facilitates rapid experimentation and A/B testing, and optimization of campaigns across multiple dimensions. One no longer needs an army of analysts to support a growth campaign- just the right combination of skills and tools. Marketing Analytics and Strategy: Gen AI has unprecedented ability to combine vast and disparate data sets to generate reliable and nuanced insights faster. It enhances the accuracy of key tools of marketers such as attribution mix modeling, media mix optimization, and Search Engine Optimization, while lowering marginal cost dramatically. It also facilitates rapid experimentation and A/B testing, and optimization of campaigns across multiple dimensions. One no longer needs an army of analysts to support a growth campaign- just the right combination of skills and tools. accuracy of key tools of marketers accuracy of key tools of marketers Automation and efficiency: McKinsey estimates that gen AI could increase marketing productivity by 5-15%, worth about $463 billion annually. The productivity enhancement is expected to happen across three dimensions: human augmentation (providing leverage to human teams, helping them scale), automated agents working alongside humans to accomplish complex tasks, and eventually, through the creation of automated teams that own significant portions of workflows. What sounded like distant future is almost here today - and the race is on to be the first and best at leveraging the potential of this technology to the fullest extent. Automation and efficiency: McKinsey estimates that gen AI could increase marketing productivity by 5-15%, worth about $463 billion annually . The productivity enhancement is expected to happen across three dimensions: human augmentation (providing leverage to human teams, helping them scale), automated agents working alongside humans to accomplish complex tasks, and eventually, through the creation of automated teams that own significant portions of workflows. What sounded like distant future is almost here today - and the race is on to be the first and best at leveraging the potential of this technology to the fullest extent. gen AI could increase marketing productivity by 5-15%, worth about $463 billion annually gen AI could increase marketing productivity by 5-15%, worth about $463 billion annually As the Gen AI landscape and capabilities evolve, adoption is expanding and new workflows and applications of Gen AI in Marketing are being uncovered rapidly. The rich entrepreneurial activity in this space is testament to the value at stake. But as the industry collectively navigates this space, it will be important to do so with adequate guardrails around privacy, and content rights - two of the most important concerns with the evolution of Gen AI. And these concerns are extremely valid and noteworthy in this space. It will be interesting to watch how industry, advocate groups and governments come together to shape this space in the coming days.

Reimagining Rev-Ops with Gen AI: Precision Marketing 

This is the second part of a series of articles on how GenAI is revolutionizing Rev-Ops functions in enterprise technology businesses. In the first part, we saw some broad applications of Gen AI in Rev Ops. In this article, we will explore how GenAI use cases are being developed and deployed in the first of the  four core Rev Ops pillars - business strategy and planning. A little bit about myself : I am a GTM veteran & Sr. Director of RevOps at Cisco. Business Planning - what is it, how is it done, and what is changing? Business Planning is the primary cross-functional performance in the corporate ballroom. Lead actors from Product, Engineering, Finance and Sales participate in this song-and-dance routine with Rev Ops called upon to choreograph the arrangement as tightly as possible. The perennial challenge in these situations is that everybody performs to their own sheets of music with not-so pleasant outcomes for the company or stakeholders. A single source of truth for business planning has historically been the holy grail of corp-strategy and execution if ever there was one. Enter language models with context awareness and generative capabilities. Generative AI enhances data-driven decision-making in business planning by providing advanced tools and capabilities that improve the efficiency, accuracy, and depth of insights. Here are some ways it contributes to this process: Democratising Data Accessibility and Usability: Generative AI makes data more understandable and accessible to people across different functions in an organization. Finally, we can move past domain specific jargons and inconsistent data structures by giving average user the ability to query and understand data in natural language. By combining this with intuitive interfaces and user-friendly data presentations, it democratizes data access and encourages a more inclusive approach to decision-making.


Real-Time Insights and Analysis: Generative AI can process vast amounts of structured and unstructured data quickly, providing executives with real-time, actionable insights. This capability allows businesses to identify trends and patterns that were previously invisible, enabling more informed decision-making.


Dynamic Scenario Planning and Modeling: Generative AI models can drastically lower the reaction times of business to emerging trends and geo-political situations, by allowing businesses to quickly simulate various scenarios and plan contingencies. This helps in testing different strategies and predicting outcomes without the need for extensive real-world experimentation.


Automation and Efficiency: While there has been a lot of discussion on AI replacing analysts and other workers, the more pertinent use case of AI in this space is in augmenting human capability. The automation of repetitive and time-consuming tasks through generative AI allows teams to focus on higher-value activities. This not only boosts operational efficiency but also supports a more agile business model that can quickly adapt to market changes. In the following articles, we will continue these discussions across Marketing, Sales, and Customer Success. This is the second part of a series of articles on how GenAI is revolutionizing Rev-Ops functions in enterprise technology businesses. In the first part , we saw some broad applications of Gen AI in Rev Ops. In this article, we will explore how GenAI use cases are being developed and deployed in the first of the  four core Rev Ops pillars - business strategy and planning. In the first part In the first part A little bit about myself : I am a GTM veteran & Sr. Director of RevOps at Cisco. Business Planning - what is it, how is it done, and what is changing? Business Planning - what is it, how is it done, and what is changing? Business Planning is the primary cross-functional performance in the corporate ballroom. Lead actors from Product, Engineering, Finance and Sales participate in this song-and-dance routine with Rev Ops called upon to choreograph the arrangement as tightly as possible. The perennial challenge in these situations is that everybody performs to their own sheets of music with not-so pleasant outcomes for the company or stakeholders. A single source of truth for business planning has historically been the holy grail of corp-strategy and execution if ever there was one. Enter language models with context awareness and generative capabilities. not-so pleasant outcomes for the company or stakeholders. not-so pleasant outcomes for the company or stakeholders. Generative AI enhances data-driven decision-making in business planning by providing advanced tools and capabilities that improve the efficiency, accuracy, and depth of insights. Here are some ways it contributes to this process: Democratising Data Accessibility and Usability: Generative AI makes data more understandable and accessible to people across different functions in an organization. Finally, we can move past domain specific jargons and inconsistent data structures by giving average user the ability to query and understand data in natural language. By combining this with intuitive interfaces and user-friendly data presentations, it democratizes data access and encourages a more inclusive approach to decision-making. Real-Time Insights and Analysis: Generative AI can process vast amounts of structured and unstructured data quickly, providing executives with real-time, actionable insights. This capability allows businesses to identify trends and patterns that were previously invisible, enabling more informed decision-making. Dynamic Scenario Planning and Modeling: Generative AI models can drastically lower the reaction times of business to emerging trends and geo-political situations, by allowing businesses to quickly simulate various scenarios and plan contingencies. This helps in testing different strategies and predicting outcomes without the need for extensive real-world experimentation. Automation and Efficiency: While there has been a lot of discussion on AI replacing analysts and other workers, the more pertinent use case of AI in this space is in augmenting human capability. The automation of repetitive and time-consuming tasks through generative AI allows teams to focus on higher-value activities. This not only boosts operational efficiency but also supports a more agile business model that can quickly adapt to market changes. Democratising Data Accessibility and Usability: Generative AI makes data more understandable and accessible to people across different functions in an organization. Finally, we can move past domain specific jargons and inconsistent data structures by giving average user the ability to query and understand data in natural language. By combining this with intuitive interfaces and user-friendly data presentations, it democratizes data access and encourages a more inclusive approach to decision-making. Democratising Data Accessibility and Usability: Generative AI makes data more understandable and accessible to people across different functions in an organization. Finally, we can move past domain specific jargons and inconsistent data structures by giving average user the ability to query and understand data in natural language . By combining this with intuitive interfaces and user-friendly data presentations, it democratizes data access and encourages a more inclusive approach to decision-making. average user the ability to query and understand data in natural language average user the ability to query and understand data in natural language Real-Time Insights and Analysis: Generative AI can process vast amounts of structured and unstructured data quickly, providing executives with real-time, actionable insights. This capability allows businesses to identify trends and patterns that were previously invisible, enabling more informed decision-making. Real-Time Insights and Analysis: Generative AI can process vast amounts of structured and unstructured data quickly, providing executives with real-time, actionable insights . This capability allows businesses to identify trends and patterns that were previously invisible, enabling more informed decision-making. real-time, actionable insights real-time, actionable insights Dynamic Scenario Planning and Modeling: Generative AI models can drastically lower the reaction times of business to emerging trends and geo-political situations, by allowing businesses to quickly simulate various scenarios and plan contingencies. This helps in testing different strategies and predicting outcomes without the need for extensive real-world experimentation. Dynamic Scenario Planning and Modeling : Generative AI models can drastically lower the reaction times of business to emerging trends and geo-political situations, by allowing businesses to quickly simulate various scenarios and plan contingencies. This helps in testing different strategies and predicting outcomes without the need for extensive real-world experimentation. Dynamic Scenario Planning and Modeling Dynamic Scenario Planning and Modeling Automation and Efficiency: While there has been a lot of discussion on AI replacing analysts and other workers, the more pertinent use case of AI in this space is in augmenting human capability. The automation of repetitive and time-consuming tasks through generative AI allows teams to focus on higher-value activities. This not only boosts operational efficiency but also supports a more agile business model that can quickly adapt to market changes. Automation and Efficiency: While there has been a lot of discussion on AI replacing analysts and other workers, the more pertinent use case of AI in this space is in augmenting human capability. The automation of repetitive and time-consuming tasks through generative AI allows teams to focus on higher-value activities. This not only boosts operational efficiency but also supports a more agile business model that can quickly adapt to market changes. In the following articles, we will continue these discussions across Marketing, Sales, and Customer Success.

Reimagining Rev-Ops with Gen AI: Always-On Strategy and Planning 

Generative Intelligence, or Gen AI, is on its way to revolutionize almost every aspect of “work” as we know it, be it bringing products to life, getting them to the hands of customers, after sales support, or other corporate functions. Revenue Operations or Rev Ops, in many ways a more recent addition to the list of functions, especially in B2B tech, is a prime target for disruption by Gen AI. A little bit about myself - I am a Sr. Director of Rev Ops at Cisco. Here is my LinkedIn profile ; prior to Cisco, I was a consultant at McKinsey, with a background in Industrial Robotics and Electrical Engineering. Before we go too deep, what is Rev Ops, and how is it different from Sales Operations? Sales Operations: Focuses on optimizing existing revenue streams by helping sales reps improve sales efficiency and effectiveness.
Revenue Operations: A strategic function that integrates and aligns business planning, marketing, sales, and customer success. Rev Ops seeks to break down the traditional siloed approach within go-to-market with a more holistic approach that drives revenue growth and customer outcomes with end to end integration and optimization of data & insights, tech stack, and customer interactions. Generative AI, with its multi-modal capabilities (text, image, voice, audio) presents a unique and never-before opportunity to optimize and reimagine workflows across Rev Ops. Even within the now-familiar hype-train, we have started seeing real and tangible examples of successful adoption of Gen AI in this space which makes it extremely risky for anyone to ignore the possibilities. In fact, once you move past the meme-generative use cases of Gen AI, Rev Ops might be one of the few areas where the hype might be real - with potential to digitize, automate, and scale capabilities rapidly with readily available tech. To highlight a few: Data-Driven Decision Making: Siloed data architecture and the high cost of integration has been one of biggest hurdles for organizations to leverage proprietary data. Generative AI, with its context learning and real-time augmentation capabilities,  enables organizations to stitch large and diverse data sources together and generate valuable insights quickly to inform decision-making. This is a gamechanger for identifying trends, customer preferences, and market dynamics, which leads to more accurate business plans, investment allocation, forecasts, and targeted strategies.
Dynamic Personalization and Targeting: AI can create hyper-personalized content and recommendations for customers, lowering customer acquisition cost, improving conversion rates, and ultimately resulting in higher customer satisfaction. RevOps teams can tailor their approaches to meet rapidly evolving customer expectations.
From Enablement and Automation to Redesign: This one is not new - automating repetitive tasks through process automation has been around for a while. What Gen AI adds is the ability to learn from tasks across teams to redesign entire workflows. We are no longer talking about reducing the number of steps in a workflow- we are squarely in the realm of streamlined workflows across functions, and automated agents that works side-by-side with humans.
Enhanced Sales and Marketing Collateral: AI tools can generate high-quality sales and marketing materials, such as enriched product descriptions and demos (with images, video, and audio), and email campaigns, quickly and consistently. This enables teams to present a more compelling and personalized story for their brands across diverse buyer personae quickly and at-scale.
360 degree customer view, scoring, and qualification: Advanced algorithms in generative AI can analyze data from multiple sources to generate a true 360 degree view of customers, enhancing lead understanding and quality, enabling sales teams to prioritize efforts dynamically. In the following articles, we will take a closer look at how these capabilities and use cases come together across the 4 pillars of Rev-Ops: Planning, Marketing, Sales, and Customer Success. Generative Intelligence, or Gen AI, is on its way to revolutionize almost every aspect of “work” as we know it, be it bringing products to life, getting them to the hands of customers, after sales support, or other corporate functions. Revenue Operations or Rev Ops, in many ways a more recent addition to the list of functions, especially in B2B tech, is a prime target for disruption by Gen AI. to revolutionize almost every aspect of “work” to revolutionize almost every aspect of “work” is a prime target for disruption is a prime target for disruption A little bit about myself - I am a Sr. Director of Rev Ops at Cisco. Here is my LinkedIn profile ; prior to Cisco, I was a consultant at McKinsey, with a background in Industrial Robotics and Electrical Engineering. LinkedIn profile LinkedIn profile Before we go too deep, what is Rev Ops, and how is it different from Sales Operations? Sales Operations: Focuses on optimizing existing revenue streams by helping sales reps improve sales efficiency and effectiveness. Revenue Operations: A strategic function that integrates and aligns business planning, marketing, sales, and customer success. Sales Operations : Focuses on optimizing existing revenue streams by helping sales reps improve sales efficiency and effectiveness. Sales Operations Revenue Operations : A strategic function that integrates and aligns business planning, marketing, sales, and customer success. Revenue Operations Rev Ops seeks to break down the traditional siloed approach within go-to-market with a more holistic approach that drives revenue growth and customer outcomes with end to end integration and optimization of data & insights, tech stack, and customer interactions. Rev Ops Rev Ops Generative AI, with its multi-modal capabilities (text, image, voice, audio) presents a unique and never-before opportunity to optimize and reimagine workflows across Rev Ops. Even within the now-familiar hype-train, we have started seeing real and tangible examples of successful adoption of Gen AI in this space which makes it extremely risky for anyone to ignore the possibilities. In fact, once you move past the meme-generative use cases of Gen AI, Rev Ops might be one of the few areas where the hype might be real - with potential to digitize, automate, and scale capabilities rapidly with readily available tech. To highlight a few: we have started seeing real and tangible examples of successful adoption of Gen AI in this space we have started seeing real and tangible examples of successful adoption of Gen AI in this space Data-Driven Decision Making: Siloed data architecture and the high cost of integration has been one of biggest hurdles for organizations to leverage proprietary data. Generative AI, with its context learning and real-time augmentation capabilities,  enables organizations to stitch large and diverse data sources together and generate valuable insights quickly to inform decision-making. This is a gamechanger for identifying trends, customer preferences, and market dynamics, which leads to more accurate business plans, investment allocation, forecasts, and targeted strategies. Dynamic Personalization and Targeting: AI can create hyper-personalized content and recommendations for customers, lowering customer acquisition cost, improving conversion rates, and ultimately resulting in higher customer satisfaction. RevOps teams can tailor their approaches to meet rapidly evolving customer expectations. From Enablement and Automation to Redesign: This one is not new - automating repetitive tasks through process automation has been around for a while. What Gen AI adds is the ability to learn from tasks across teams to redesign entire workflows. We are no longer talking about reducing the number of steps in a workflow- we are squarely in the realm of streamlined workflows across functions, and automated agents that works side-by-side with humans. Enhanced Sales and Marketing Collateral: AI tools can generate high-quality sales and marketing materials, such as enriched product descriptions and demos (with images, video, and audio), and email campaigns, quickly and consistently. This enables teams to present a more compelling and personalized story for their brands across diverse buyer personae quickly and at-scale. 360 degree customer view, scoring, and qualification: Advanced algorithms in generative AI can analyze data from multiple sources to generate a true 360 degree view of customers, enhancing lead understanding and quality, enabling sales teams to prioritize efforts dynamically. Data-Driven Decision Making: Siloed data architecture and the high cost of integration has been one of biggest hurdles for organizations to leverage proprietary data. Generative AI, with its context learning and real-time augmentation capabilities,  enables organizations to stitch large and diverse data sources together and generate valuable insights quickly to inform decision-making . This is a gamechanger for identifying trends, customer preferences, and market dynamics, which leads to more accurate business plans, investment allocation, forecasts, and targeted strategies. inform decision-making inform decision-making Dynamic Personalization and Targeting: AI can create hyper-personalized content and recommendations for customers, lowering customer acquisition cost, improving conversion rates, and ultimately resulting in higher customer satisfaction. RevOps teams can tailor their approaches to meet rapidly evolving customer expectations. hyper-personalized content hyper-personalized content From Enablement and Automation to Redesign: This one is not new - automating repetitive tasks through process automation has been around for a while. What Gen AI adds is the ability to learn from tasks across teams to redesign entire workflows . We are no longer talking about reducing the number of steps in a workflow- we are squarely in the realm of streamlined workflows across functions, and automated agents that works side-by-side with humans. redesign entire workflows redesign entire workflows Enhanced Sales and Marketing Collateral: AI tools can generate high-quality sales and marketing materials, such as enriched product descriptions and demos (with images, video, and audio), and email campaigns, quickly and consistently. This enables teams to present a more compelling and personalized story for their brands across diverse buyer personae quickly and at-scale. This enables teams This enables teams 360 degree customer view, scoring, and qualification: Advanced algorithms in generative AI can analyze data from multiple sources to generate a true 360 degree view of customers, enhancing lead understanding and quality, enabling sales teams to prioritize efforts dynamically. Advanced algorithms in generative AI can analyze data from multiple sources Advanced algorithms in generative AI can analyze data from multiple sources In the following articles, we will take a closer look at how these capabilities and use cases come together across the 4 pillars of Rev-Ops: Planning, Marketing, Sales, and Customer Success.

Reimagining Revenue Operations with Gen AI

You are a developer; you have been stuck at your DevOps job for over 3 years. You’ve never really liked the DevOps in big companies, either. However, you have strong communication skills, a knack for management, and a passion for innovation that so few of your colleagues have. You constantly think of pivoting to new career paths in tech, whether that’s frontend, project manager, developer relations, or even waiting to get promoted to UX design. That sounds very nice; in fact, it is all very achievable. But that’s not what you would want, is it? You see yourself as a pioneer, a trendsetter; one might even say as a founder. If you see yourself as a founder or just love the idea of startups, you no doubt ponder your business and entrepreneurial ideas actively. In the tech world, there are always trends in startups regarding what startups of a particular time are building. In the 2010s, there were startups focused on mobile apps. In 2020-2022,  there were startups all focused on Web3 and decentralized technologies. In 2023, we can most definitely conclude the startup trend to be SaaS-based. This is where the new career path of DevOps is entrenching itself. What Is SaaS? There are a lot of sources that give the exact definition, but let's define it ourselves. Formally, SaaS stands for Software-as-a-Service. This is software that you rent out or make available for monetary purchase. You made this software as a service that people are paying for. What is so special about SaaS businesses? Two main reasons. SaaS businesses make the most consistent amount of money, and making a SaaS business has never been easier. These two factors make SaaS very alluring to every would-be IT entrepreneur. How do we know this to be true? According to Clara LoCricchio of firstpagestrategy.com: In 2023, the SaaS market grew significantly to an esstimated 273.5 Billion. A 13.6% increase over 2022. This statistic is as accurate as Bitcoin’s price fluctuations. SaaS is one of the fastest-growing branches of the tech industry. In terms of monetization, competing parts of the tech industry are subscription-based and ad-revenue-based software types. SaaS is the growing king among these 3 software monetization giants. What Is DevOps? According to Amazon Web Services (AWS): Under a DevOps model, development and operations teams are no longer “siloed.” Sometimes, these two teams are merged into a single team where the engineers work across the entire application lifecycle In short, someone with a DevOps role is essentially doing something on the software solutions team (or one of the tech teams) and works in tandem with management, customer service, or even marketing. You might ask yourself, “As someone on the DevOps career path, why should I care about SaaS?” SaaS companies are where DevOps positions and roles shine the brightest and are most helpful. That is where you can make the best impact. Now, let us look at the 3 ways you could do that. Before we get into the list, if you want a refresher on the different DevOps types, here is a link to an article I wrote on them, aptly titled “Your Guide to The Suits of DevOps.” 1. IaaS & PaaS: Both PaaS and IaaS are sub-branches of SaaS. PaaS stands for Platform-as-a-Service, and IaaS stands for Infrastructure-as-a-Service. PaaS are web services that do certain or many web activities for the user instead of you doing or making them yourself. IaaS sells the user necessary infrastructure elements to help in the construction and services of their web-based projects. For a more detailed explanation, see . www.paddle.com , the PaaS global market cap is expected to rise significantly, and in the year 2023, it will be 115 Billion USD. IaaS is projected to reach a 110 Billion USD market cap by 2024. Why is this important? According to Statista This is important because, as a person in DevOps, your skills will be ever more needed. IaaS and PaaS services require a lot of customer service analysis and marketing that can adequately convey the complexities of the technologies in simple terms. If you are a DevOps personnel specifically working with networks or the main dev team as well as customer service or marketing…..then IaaS and PaaS companies are in your interest to pay attention to. 2. Generative AI: , Generative AI is Artificial Intelligence that, depending on its use case, can produce digital pieces of text, imagery, audio, and, at times, synthetic data. According to techtarget.com How does generative AI fit into DevOps? Most DevOps jobs touch on or even wholly focus on automation tasks. Some DevOps professionals solely focus on automating tasks within their assigned teams. Generative AI completely changes the automation game. e.g., DevOps working with the development team and marketing. They use generative AI to speed up their marketing tasks (slogans, tutorial scripts, social media post text). They can also use generative AI to help with code testing. 3. RevOps Relevance: As DevOps career pathways increase in complexity and depth, their ways of doing things also change. What do I mean? The DevOps personnel may feel a stronger affinity for their company's tech or programmatic side, but this doesn't mean the humanities side of their area is ignored. This is evidenced by the introduction of RevOps as a DevOps integration strategy. What is RevOps? , Revops can be defined as: According to techtarget.com The strategic integration of sales, marketing and service departments to provide a better end-to-end view to administration and management, while leaving day-to-day processes within the departments. I know what you are thinking, “Isn’t RevOps its own department and job type?” Yes, it is. Even so, this means DevOps roles, which intersect with the marketing or sales departments, will then be required to do more in these departments rather than focus more on the development departments. It also means if you currently have a position in a DevOps role and want to transition into a similar job but more focused on the humanities part, then this is for you. As a DevOps developer, you must know that your job may become more tech-focused soon as RevOps job roles grow and gain traction. It is important to remember both significant and minor SaaS companies have noticed these 3 crucial trends in the industry. IaaS & PaaS are soon to be the most successful subsets of SaaS. RevOps will emerge as a job position, even siphoning some DevOps role responsibilities. Not to mention generative AI. It will be the biggest disruptor in the DevOps roles as it quite literally improves every process of all technical automation processes. One question does remain….how ready are you as a DevOps developer for SaaSy 2024? Feature image from saasmarketer.io

3 Ways DevOps Developers Can Gain from 2024 SaaS Growth

Let’s say your KPIs are falling down and you realize there is something wrong looking at your metrics dashboard. Sales reps have started to struggle to convert the leads brought by the marketing team, and customer success is doing a bad job of identifying the proper upsells. Something is going wrong, your left hand doesn't know what your right hand is doing. B2B buyers nowadays are brighter than ever, in other words, they are doing their own research before even your welcoming email pops into their inbox. So… Not to mention the length of the B2B sales cycle. in this article, we are going to walk through one of the popular business frameworks- Revenue operations (RevOps)-that accelerate revenue growth by aligning a customer-focused approach in marketing, sales, and customer success management What is Revenue Operations? Simply, RevOps is a business structure that involves customer touchpoints in a manner that allows company people to work collaboratively and utilize processes and tools to enhance the customer lifecycle. customer touchpoints or revenue drivers are the departments that have a direct relationship with customers. In many businesses, those departments are marketing, sales, and customer success. RevOps is a transition from decentralized to centralized management that encourages the staff to operate collectively to obtain steady growth, and what is actually meant by steady growth is Revenue and a maximized customer lifetime value. RevOps VS.  Sales OPs To get rid of the confusion before we dive in, let’s mention the difference between RevOps and Sales Ops. focus on driving the highest productivity level from the sales department. Sales Operations: while RevOps leaders care about this matter, they also try to push that level of productivity by aligning departments with each other to maximize overall performance. says Revenue operations can be seen as the merging of sales, marketing and customer success operations; however, I view rev ops more as a natural evolution where organizations are seeing value in merging the strategic aspects of various operation teams while leaving the day-to-day administrative structures of marketing, sales and customer success teams somewhat intact. Dheer Gupta What does it mean to have a RevOps function within an industry that is forecasted to grow up to and is highly competitive, low efficiency and a misalignment between revenue drivers are game-over situations. 591.8 billion in 2023 and those who adopted a RevOps function seem to be satisfied with the outcomes. According to a , top b2b saas companies have reported a 10% to 20% increase in sales productivity, the same study share that study conducted by BCG 100% to 200% increases in digital marketing ROI 10% increase in lead acceptance 15% to 20% increases in internal customer satisfaction 30% reductions in GTM expenses Those stats are really impressive, so let’s see how to drive these kinds of numbers with a closer look. Aligning marketing and sales Marketing brings leads. Sales convert and close. Well, life isn’t that easy. On average, are invalid or incomplete, and at the same time, reps’ time is wasted due to inaccurate contact data. 40% of leads 27.3% of sales Regardless of the maturity and effectiveness the marketing team has. The one thing that comes to mind looking at these stats is a misalignment between marketing and sales. Modern days B2B buyers are extremely different as we discussed above. Considering this, marketing and sales shouldn’t operate in their own silos where probably everyone has different processes or even objectives. Under the RevOps umbrella, aligning marketing and sales is one of the first issues to be taken care of. How? here is how Evaluating Marketing qualified leads vs Sales qualified leads. Many companies assess marketing and sales performance separately after looking at the revenue generated at the end of the quarter. Here is the thing, to see if your marketing and sales teams align and share the same objectives take the ratio of MQL- marketing qualified leads- to sales-qualified leads. If the result falls under , then marketers and sales reps should meet up and try to define what are the high-quality leads for the company’s product. 50% The marketing team shouldn't be proud of itself for hitting the goal of MQL if sales reps are way much lower than their revenue target. Here is a perfect example of sales and marketing alignment by , Director of RevOps in Zapier Lindsay Rothlisberger each week, our RevOps team does a walkthrough of the top high-value, closed-won deals for our colleagues in Product and Marketing. This provides a more detailed glimpse into the customer journey by sharing how the customer came to us and how they engaged with Sales. to put it in one sentence, marketing must be accountable for revenue targets as well Having RevOps software as a single source of data. RevOps software automates and centralizes sources of customer data to a single source where revenue-drivers can use to Have actionable insights automate data to get rid of repetitive tasks and save time Better predictability of market trends and customer behavior Track sales and market trends ensure the quality of useable data It is overwhelming for many decision-makers to attribute customer data from marketing automation software to sales CRM to eventually come up with an interpretation. Having a single source of truth for both sides has been very helpful. According to companies that align people, processes, and technology tools across their marketing and sales teams, report 36% more revenue growth and up to 28% more profitability. Forrester The best RevOps software tools should allow you to connect your data source in a single place to have the Eye-bird that helps you see the whole picture and make better decisions. Here is a list from Setsail of the best 11 RevOps software Establishing the Chief Revenue Officer structure. You need to have an intellectual person who oversees whether there is a correlation between sales and marketing or not. Yes, CMO can do this, but according to , many businesses say that having a CRO that aligns departments and processes has been very effective. BCG To see it clearly look at the stats from Clari why is that increase? It is obvious and we have mentioned it. B2B buyers nowadays can reach alternative pages in seconds, and see the comparison pages that affect their decisions. What happens after the sale is just as important as what happens before. See…? Correlation and transparency between customer touchpoints are becoming major issues in the competitive fields, and the best way to deal with them is to have a strong CRO or RevOps director. Now, let’s see how customer success management operates with the framework. The Roles of Customer success management in RevOps Attract, Convert, and maintain. We have now covered the correlation between attracting and converting by discussing marketing and sales alignment. Time to see how CSMs -Customer success managers- go beyond to empower the overall procedure. Customer success management is the growth engine of any subscription-based saas company. It is about enhancing the customer experience with upsells and delivering the maximum value to ensure the healthiness of the customer's lifetime. In RevOps things get really exciting with CSMs after jumping on the pathway with folks from marketing and sales to push up revenue metrics. So, here is the Role of CSMs in the context of Revenue operations. 1. Customer Data One of the primary roles of CSMs is data, they analyze it the come up with interpretations such as: Where they analyze customer behavior and engagement patterns to predict the likelihood of contract renewals. They also create renewal playbooks that outline the steps and touchpoints required to ensure a smooth renewal process. Renewal forecasting: CSMs assess account health by evaluating key metrics and indicators, like effective product usage, customer satisfaction scores, and any potential risk of customer churn. Account health: This is one of the essential metrics that measure customer loyalty and the likelihood of customers recommending the services of the company to colleagues. CSMs prepare a set of questions as a survey to be scaled from 1-10. Net Promoter Score (NPS): These results are not meant to be stored somewhere in CSM’s drive. For example, a CSM can identify an underutilized feature of a product and reach out to that customer to provide training to sustain the level of engagement. 2. Process tracking. to enhance customer experience, CSMs should have some proactive approaches like: reaching out to customers regularly to check in on their progress. address any concerns or offer guidance. working collectively with marketing, sales, and product management to align efforts and provide consistent customer experience. Maybe the customer doesn’t need training for that specific feature of the product, it could a problem from the root of it. CSMs shouldn’t try to figure out conflicts on their own, that’s why, walking the product team through these concerns can eventually show up what is the real issue. 3. Determining opportunities CSMs should always work on supporting the customer base by setting goals to multiply the value: For example, CSMs can set a goal of reducing churn rate by 10% within a timeframe and collaborate with teams to increase engagement levels with risky customer accounts by providing personalized support. CSMs also engage in workforce planning to determine any staffing issues, or to show a need for a tool that could be used to benefit the customer lifecycle. 4. leveraging systems and tools CSMs are responsible for managing and implementing the tools that support customer success efforts. This includes CSM-specific tools for managing customer interactions and workflows, as well as taking ownership of customer-related data in the CRM system used by other departments. A CSM might configure and customize a CSM tool to track customer health scores, automate notifications for high-risk accounts, and streamline the workflow for customer touchpoints. To sum it up, customer success management seems to be the backbone of the marketing and sales alignment. CSMs support sales reps by taking care of the converted customers, and provide the seamless value marketing team used to attract those prospects The Bottom line. Revenue Operations emerge as a powerful framework that brings together marketing, sales, and customer success management under a unified goal. by aligning these three departments with each other, you can streamline your operations and have a clear vision. But here is the thing, you won’t be able to proceed with RevOps if you didn’t choose the right people who work collaboratively to achieve organizational goals. And if you have a perfect crew who can operate with high morale and work collectively, RevOps framework could be your B plan to accelerate revenue growth and move up your KPIs needles. Cheers

Marketing, Sales, and Customer Success Management From a RevOps Scope

Startups of The Year: Meet the AI Industry

İlin startapları: Süni intellekt sənayesi ilə tanış olun

Startups del año: conozca la industria de la IA

استارت آپ های سال: با صنعت هوش مصنوعی آشنا شوید

वर्ष के स्टार्टअप: एआई उद्योग से मिलिए

Startups pou ane a: Rankontre endistri AI

סטארטאפים של השנה: הכירו את תעשיית הבינה המלאכותית

今年のスタートアップ: AI 業界を知る

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Startups of the Year: Hihaona amin'ny indostrian'ny AI

वर्षको स्टार्टअपहरू: एआई उद्योगलाई भेट्नुहोस्

Стартапи року: знайомство з індустрією ШІ

Yil startaplari: AI sanoati bilan tanishing

B2B purchasing behaviour has shifted dramatically in recent years. As a result, businesses have had to quickly adapt to how they interact with potential clients as the traditional sales process that defines a prospect's buying path has been turned upside down. Marketing, Sales, and Customer Success — these three distinct departments have a significant influence on revenue, but when each department begins to center their attention on their individual growth, it's easy for them to miss out on opportunities and for customers to lose out on a unifying buying experience. It's quite necessary therefore for these departments to come under a single entity as many companies have come to realise that a siloed strategy is no longer viable. This alignment brings about the subject of Revenue Operations. What Is Revenue Operations? Revenue operations (also known as RevOps) is the business practice of driving revenue across teams. Revenue operations have one purpose, and that is to boost predictable revenue and streamline processes across marketing, sales, and customer successes. This results in increased revenue growth due to increased revenue team efficiency. Why Is Revenue Operations So Important? There are three crucial elements to note when it comes to aligning — People, Data, and Processes. People Suppose you have marketing, sales, and customer success departments. It's known that the goal of the marketing department is to generate leads for the sales department, who will, in turn, make an effort to turn those leads into sales. The converted customers are then handed over to the customer success team. As a result, each team has its own set of KPIs and targets to achieve. But this can lead to a major flaw in revenue growth, in that your marketing team may be capable of generating a huge number of leads for sales but what if the leads generated are of poor quality? Does it probably mean that the sales team is wasting time on leads that are unlikely to convert? This same logic also applies to the customer success team. Marketing sends the leads to Sales, which is responsible to close the sale and then will frequently hand that closed sale over to Customer Success. But there is not much collaboration between the Sales and Customer Success team to know how to increase revenue from those customers. Data Data is the lifeblood of any business. Any organisation having revenue growth in mind must know how to handle and derive insights from data. There'll likely be a major disconnect when the Marketing, Sales, and Customer Success Department follow a siloed system. Each department looking at a different set of data is not helping. Processes Communication is a critical element here. With each team having individual metrics and processes, keeping track of huge teams and enormous amounts of leads and clients can be difficult. As a result, it is important to adopt revenue operations as it enables you to unite your team under a single vision and offer them a single goal to achieve. Revenue operations help align teams and departments with the company’s goals and strategy, drive top-line growth and increase profitability. It is also an integral part of managing customer relationships. Revenue Operations allow you to streamline your processes and guarantee that everyone on your team is on the same page. How To Know When It's Time To Invest In RevOps? Knowing when to delve into RevOps is critical for the success of any business. However, one does not just simply go into RevOps simply because it's working for another organisation. It's essential to know when to invest in it and start working on a RevOps strategy. The following 3 Questions (based on the above People, Data, and Processes) will help you know whether it is this is the right time to invest in RevOps: Are you experiencing Tool Overload? With recent developments in automation, a lot of tools are being used to ease the sales process. When you find your company employing the use of these many tools and they do not communicate well, that's a call to align your tech stack into one centralised tool. Are your data insights adding up? Having distinct data results from different departments can be a real mess. A RevOps team helps you avoid this while having a consolidated view of your data. Are my processes up to date and able to be scaled? For today's fast-paced industry, business processes must constantly adapt and remain informed and prepared. A RevOps team assembles the required people to keep processes current and adaptive. Ready To Delve Into RevOps? Now once you have decided that it's time to delve into RevOps, it all boils down to building your team and providing training for them. You can decide to hire a RevOps specialist, one with a sales operations background, who knows how to work with marketing software tools, optimise sales, organise and analyse company data, and with extensive experience in creating scalable cross-functional processes and workflows. Or you can just go along with an already-trained team of professionals that will be able to immediately assist your company.

Revenue Operations Are Making Businesses Stay Ahead Of The Curve: See how and when to invest in it

In a recent Emissary survey of executive-level tech buyers, 85% of recent, major tech purchases included a non-technical buyer with major influence over the final decision. This trend results in additional pressure on sales and marketing organizations to speak the business language of their prospects and customers, not just demonstrate technical expertise. A strong strategy using vertical marketing best practices can help reach these cross-functional buyers, drive inbound leads, and help solution providers differentiate themselves in crowded markets. Most vertical marketing strategies are light in nature consisting of tabs on websites, vertical-oriented stock photos, and keywords added to headers. The best tech marketers, however, go much deeper. Here is what the best do differently: Vertical marketing best practice #1: Resist getting starry-eyed over huge markets. The first step in vertical marketing is deciding which industries to target. This involves checking the CRM and other systems of record. Where are the most revenues derived from? And where are relationships the deepest and longest-held? You will also want to keep in mind where you have the best chance of getting testimonials or branded case studies. But don’t just look at historical data. Cast a broader net to look at propensity to buy in new industries where you might not have a foothold today. As you review your analysis, be careful of sorting exclusively to exceptionally large industries. Sure. They have massive potential by virtue of the fact that they consist of large numbers of companies. However, if you go too large, you may end up with segment definitions that are too broad to be useful. You want to be sure that the verticals you select are narrow enough that your targets recognize themselves in the group of accounts. The key to everything is personalization. Good vertical choices for vertical marketing use similar jargon. Do the accounts in your chosen vertical use the same shorthand and terminology? This allows you to write for a segment. Another good sign that you’ve identified a vertical worth marketing to is that it consists of self-referencing members. To optimize your investment, consider whether the accounts in a vertical look to each other as reference points. Do they consider each other peers, role models or competitors? The final clue has to do with the environment that surrounds the vertical. You’re looking for a group of accounts experiencing the same market conditions (regulations, consumer behaviors, and economic factors) in the same way. These criteria may help you narrow in on smaller groups of accounts. For example, instead of just focusing on an industry such as “Financial Services,” you may be better off focusing on a sector such as Insurance. Instead of “Retail,” you may get more leverage out of strategies focused on home goods, clothing, or pharmacies. Vertical marketing best practice #2: Listen first. Then speak carefully. In some companies, ‘vertical’ is an overarching strategy starting with product development. Products designed for industry-specific applications are, by definition, consumed by specific industries. In this case, there are likely many vertical SMEs inside the organization that can help marketers refine their vertical approaches. It’s tougher to design your approach when your organization’s vertical strategy is more about go-to-market than it is about the product. In those cases, products are the same across industries. As a result, you might find that you don’t have a lot of in-house vertical expertise. This is particularly challenging in the tech world because you must communicate a lot of experts, technical information to your prospects and clients. Layering in an additional vertical-specific context can make for dense and intelligible messaging. Aim for enough vertical context to make your message resonate but not so much that you expose your lack of expertise and end up sounding like an outsider. The best tech marketers create this balance by doing extensive research on verticals before nailing down the audience, message, and delivery. This can include: Attend trade shows to look for common themes and identify business issues. Get familiar with the terminology and jargon used by insiders. In addition, join social media groups and discussion threads to look for tone and topics that encourage engagement. Events and networks. . Go beyond bookings. See if there are common customer complaints among sector members. You may also mine themes from highly satisfied customers. In-house data Leverage external experts to clue you into themes, unresolved issues, placement options and more. And use Emissary Industry Insider Guides to key in on critical differences.
The additional time spent in the research phase is worth it. At best, poorly executed vertical marketing is ineffective. At worst, it can alienate your target by making you look out of touch. Outside coaches. Vertical marketing best practice #3: Take another look at who’s who. Another upgrade to your vertical marketing includes revisiting your persona profiles to ensure that they are completely fleshed out with needs, common pain points, job tasks, behavioral patterns, and KPIs as well as anything other relevant psychographic or demographic information. In the tech space, it’s tempting to focus exclusively on core IT roles such as Director of Infrastructure or Cloud. They may be the closest to the actual use of your solution and their issues are likely to be similar across industries. E.g., the accuracy of data, security, speed of processing, etc. But as you take a more vertical approach, you may need to include business-oriented decision-makers. For example: Product leaders in medical device companies invest heavily in building new technology-enabled products and invest in technology enhancements to upgrade existing products.
Customer experience executives in retail will drive huge budgets focused on digital fulfillment impacting the core tech stack. Commercial executives in professional services firms spend money to spur market growth opportunities. Their expansion counterparts, Customer success teams, may require specific data or resolutions to common client complaints. Production leaders or quality control personnel in manufacturing carry notable weight. They will be concerned with errors, downtime, and productivity. Similarly, Facilities leaders worried about uptimes and evolution to smart factories. Purchasing executives in CPG work with their peers in operations and finance to balance amassing inventory liabilities with the risk of missed bookings due to shortages. All may find incredible value in applying your technology to their specific business problem. The most successful tech marketers add more definition to their target audience and further refine their messaging by exploring additional personas outside of core IT that are relevant in specific verticals. Vertical marketing best practice #4: Don’t stop with content. The next vertical marketing best practice has to do with breadth. Most vertical marketing strategies start with content for demand generation and SEO activities. In the early phases, this usually involves creating superficial skins for existing content. E.g., substituting page headers and images into existing copy. The next step is to deepen content with net new copy specifically focused on business issues that are relevant to an industry and to your expanded set of personas. The output is fully new web pages, new collateral, and vertical case studies. The best tech marketers take it even further and extend vertical approaches across their major marketing initiatives. Other elements of your marketing motions that can be verticalized include: Build a one-to-many ABM campaign aimed at a vertical. These can include emails, direct mail, customized landing pages, and more. ABM. Not only should you add vertical conferences to your calendar, but you can also create your own. Utilize vertical SMEs as panel guests in client-facing events. They are a draw to prospects and represent instant credibility. Events. In addition to website content and SEO, you can utilize vertical-specific elements in paid social ads, display ads, and press placements to gain awareness in a vertical. Outbound. Equip your outbound team with vertically oriented lists, email copy, and collateral to multiply impact by combining inbound and outbound activity. Promotion. Vertical marketing best practice #5:  If you market to verticals, sell to them too. It wouldn’t be a marketing blog if we didn’t take a moment to bemoan the continued misalignment of sales and marketing in technology companies. Although arguably this has gotten better over the years, there are still disconnects in many (most?) organizations when it comes to alignment on target accounts, sales-worthy content, value messaging, the definition of a lead, and more. One thing we see the best tech marketers do is to share their hard vertical work with their sales counterparts. Sales enablement is one key beneficiary. Make sure that your sellers have access to all the work that you did to identify accounts, personas, messaging, and delivery. This same information can help them develop prospecting emails, proposals, and account plans. Your sales enablement partners can incorporate vertical training into onboarding, sales kick-offs and other development activities. You can also assist them with vertical-oriented sales content beyond the case studies and collateral mentioned earlier. Vertical-oriented skins for presentation decks can add a layer of relevance in key sales interactions. Sales operations (increasingly evolving into Revenue Operations or RevOps) is another group on the lookout for insights. Your work can help your commercial ops teams as they analyze markets, assign territories, and define channel strategies. Aligning to similar points of view is one way to keep sales and marketing moving in the right direction. Vertical marketing best practice #6: Measure. No really.  Measure. As you read this blog, it becomes clear that the best tech marketers are investing more time and budget into their vertical marketing strategies than their less successful peers. As a result, it’s worth tracking program-specific KPIs tied directly to your vertical marketing strategies to determine the payback of those investments. Options include: Identification and engagement with key vertical personas Consumption of vertical-oriented content Press pickup and placements Leads generated within vertical Conversion ratios, velocity Pipeline in vertical Average contract value. Still considering an upgrade to your vertical marketing strategy? Vertical approaches offer significant impact given the increasing need for business-level marketing and selling in the space. But it’s not a decision to make lightly. Vertical marketing requires more research and context than any other element of your marketing strategy. Follow the best practices laid out by those who have learned the hard way. Be thoughtful. Start small. And keep maturing your approach along the way.

6 Vertical Marketing Best Practices for the Tech Industry

The Customer Success Operations (CS Ops) role is critical in delivering, optimizing, and maintaining successful tech-touch programs, ensuring that everything runs smoothly. However, it can be a daunting task, especially if you’re just getting started. CS teams are expanding and new roles are emerging. Since CS is maturing as a specialty, roles (specifically) like Customer Success Operations (CS Ops) are gaining upper hand. Let’s try and understand why CS ops are vital in today’s day and age where everything is going remote. Defining the CS Ops role (is it really operations?) CS ops is an operations team working hand in hand with the CS team to deliver the best customer experience. The Ops team updates the existing processes for the organization. It is operations, but NOT just operations! The following points will make you understand the criticality, of the operations team for CS, better: Provides foundational execution and strategic insights to CSMs (Customer Success Managers). Breaks down silos(especially in SaaS) that have been built around different teams in the organization by aligning across different teams. Helps in CS Enablement. Gives support to the CS team to carry out data analysis. Oversees reporting and metrics tracking. Helps in identifying customer success journeys. Provides support with product analytics as well. Oversees system implementation and administration, process creation, etc is done by the CS ops team. Manages data analytics, tech-stack for CS team, key process development, strategic planning. How does a ‘CS Ops team’ work with the other ops teams? First things first, hire a person who can grow the team- be it ops or any other function. A team having certain competencies is a crucial factor to keep in mind while hiring. The teams across the organization should be aligned to work smoothly without any sort of friction. CS Ops team ensures that the data flows smoothly between all the teams, be it the marketing, sales, product, and the CS team.  Professional services Ops are also an important addition to the organization in today’s digital age. Regular catch-up, perhaps weekly, with the Marketing Ops, Business Ops, Rev-Ops, etc will ensure collaboration across the teams. This will result in shared and aligned goals of customer success- for both internal and external customers. When should the CS Ops team be brought into the picture? Start with the CS ops team early on. Most of the successful SaaS business organizations have their Ops person early on. It helps the CS team be proactive and streamlines the business operations across the organization.  Also, having the customer journey written down early exponentially grows your business. Make a case today for CS Ops- to focus on CS, if you don’t have already. The following situations beg for a CS Ops team to function: If your CS team is not being fully recognized, then you might need an operational manager and an Ops team to voice the concerns. If your CSMs are always engaged with customers-acquiring, retaining, and growing them- without the time to look into other vital matters. If your CS team is not performing at its optimal level and is unable to achieve its 100% efficiency. Since the Ops helps the business in scale and efficiency, it should be an indispensable part of your strategic position. Role of CS Ops in Digital-led CS (tech-touch) Digital-led CS (tech-touch), in these tough times-especially since the pandemic, is gaining momentum. The digital CSM has all the responsibilities of a regular CSM. In addition to those, s/he would have to be responsible for setting up for the customers. automated digital experiences The important question is to ask what digital CS is aiming at, what it means for customers, if those goals are achievable, etc. It becomes easy if you know what it means for different customer segments. Hence, CS Ops should not only be limited to SMB (small and mid-sized businesses) but should be spread across all customer segments. are important to understand in the tech-touch or the self-serve processes. For example - having a QBR with customers offline can be a 2-hour process followed by a dinner with them. However, in the case of a tech-touch customer, it’s not possible! Key experiences and moments Here you need to understand the key moments. The digital CSM would’ve to chalk out processes and programs that ensure engagement for tech-touch customers. CS ops can empower CS heads to stay more strategic, helping with executing the solution to furthermore empower CSMs to reach the best possible outcomes. The program manager (within the CS Ops team) is generally responsible for getting all those workflows up and running.  Automating success planning and user journeys, especially, for more complex customers with multiple products is vital. The point that I’m trying to make here is that understanding customer needs and creating processes around them to give them the best customer experience should be the goal. Digital-led CS Ops makes case for the following automated but data-backed decisions. Processes and metrics related to the following areas are set and measured by CS Ops:- Product Revenue Customer feedback Customer experience Tech-stack for CS Ops A tech stack or a technology stack is mostly referred to as “a bundle of practical systems and technologies that provide solutions to most of the problems faced by companies.”. It is also called the solution stack or data ecosystem. Technically, it is a mix of software and hardware bundled together to roll out a function critical to the department/business. The developers need to understand the importance of a particular function and then develop the relevant stack. The following points are mentioned to show you what many leaders from the CS world view their tech stack for CS Ops teams: CS platforms act as a Hub (where everyone can access)- to identify where the data coming from, how to link to a BI tool, where the finance data is going to be, etc. are some of the key questions to be answered. This is super critical for your CS ops team. Make sure that you have the right data about customers. Community and LMS system for customers or potential customers is an important component in a tech stack. A specific CS system is super important. Product usage/adoption, support tickets, reporting, and analytics, etc are extremely crucial to understanding your CS system as a whole. Also, when clubbed with AI platforms, like , it becomes super easy to get a 360-degree view of your customer accounts. It centralizes your data and makes the data accessible to everyone. CustomerSuccessBox The product team is usually responsible for the prioritization of building the right automation features of CS and users. Final thoughts CS Ops team is sometimes the internal advocate for several dimensions of the business. They also act as bridges between the different departments to identify the shared priorities and work collaboratively. They tend to think ahead of CS teams or other teams such as what they need and be proactive in building those bridges. CS Ops is the commonality that can be leveraged, across all businesses. Merging Ops team to build a center of excellence (CS, sales, revenue) or make their report directly to individuals. The best way is to integrate CS ops into already established teams and get marketing on board.

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