SmileDirectClub

smiledirectclub

First-Party Data is Back … With a Little Help From Its Friends. How Vectors, RAG and LLAMA 3 Are Driving a Sea Change Over the last five years, the dominant narrative surrounding data infrastructure has emphasized the importance of companies owning and leveraging their data as they acquire as much information about their users and customers as possible. Due to mounting privacy regulations, they need to gather the data themselves instead of relying on third-party data operators, such as ad networks or platforms like Google, Meta, and Amazon. Companies have fallen in line with this narrative and made the shift. But, in the battle for the best data, is first-party really better? Not by itself, but it could be with a little help from vectors, frameworks like RAG, and open-source foundation models like Llama 3. The Push for First-Party Data The argument for first-party data generally goes like this: companies need to become better stewards of data acquisition and management amid growing calls for data privacy. Consumers increasingly want to know who is hanging onto their personal information, how they got it, why they have it, and what is being done with it– and they generally don’t like the answers to those questions. Access and Delete requests are rapidly increasing, and the data privacy landscape is changing quickly. Companies are finding it hard enough to figure out their own privacy management processes; they don’t want to have to worry about third parties' as well. But the shift to first-party is not all about privacy. There is also the notion that third-party data will lose value as we move towards the proverbial cookieless future. Companies can’t get the same granular details they once could so why should they devote budget to a service that delivers less than it used to? And then there is the perpetual concern that the big platforms and ad networks will make unexpected changes. For example, they could change their algorithms, restrict access to certain types of data, or alter advertising policies in a manner that could harm a business’ performance with little or no notice. Being dependent on another company’s practices leaves one vulnerable. Companies feel stuck because they’ve already invested so much time, money, and resources into their data strategy. In this light, the push to take back control of data seems essential. But is it practical? The First-Data Problems No One is Talking About Early results for companies taking a gamble on first-party data have not met expectations. We’re seeing case after case of consumer companies that made the shift suffering. Farfetch, Allbirds, and  SmileDirectClub are just a few examples. Would better, more strategic use of first-party data turn the tide on the rising customer acquisition costs? Still, the current reliance on first-party data– and the practices to extract that data– is a commonality across several companies that are experiencing tougher times today. It’s noticeable enough to make analysts, VCs, and marketers themselves ask if they were wrong to prioritize first-party data. The downsides of first-party data, as it is currently acquired and leveraged, are often considered to be underestimating the disappearance of device IDs, changing IP addresses, consumer adoption of fake emails, and ad blockers. While true, much more significant issues are at play. First, there is a massive talent gap. Big Tech and the platform companies snag the best. They have the most to offer, making it difficult for up-and-coming consumer companies to compete for the data scientists and ML talent needed to make sense of the information being collected and analyzed. Without truly exceptional people, companies have struggled. There is also a real tooling problem. The offerings available to companies are nowhere near equivalent to the tools Big Tech companies boast internally (which can be a factor in the talent gap). Tooling makes a difference, and most companies simply can’t compete right now. Finally, there is a volume challenge. Big Tech and the ad networks have mountains of data, as these companies pool and anonymize hundreds of billions of data points to make their models run effectively. By contrast, if a company has only its data to work with, there is just not enough for ML to work as promised. While these problems seem serious, is it time to give up on the potential– and the need for– first-party data? No way! The Power of Vectors The biggest issue hindering first-party data is how companies are trying to access it. Up to this point, businesses have taken an Old World approach. Models must be built from scratch to extract the value from data that businesses require. This takes time, money, and most of all talent; it depends on how good your ML engineers and data scientists are. However, as discussed above, there is not enough available talent to make this approach work better than leveraging third-party data. The lack of talent creates the bottleneck. However, this does not mean we need to give up on first-party data. We just need to change how we approach it. In the New World that is possible today, vectors and vector embeddings are the key. Vectors are generic mathematical objects that can represent data points' features or attributes while embedding models analyze patterns in data to generate these information-packed, meaningful representations learned from data; they capture the semantic relationships. Vector embeddings are the format that can encode everything you know about a user or a customer and make that information accessible to an analytics system, or leverageable to personalize the user experience, or even to catch fraud. There are so many possibilities. Vectors are poised to drive a sea change because they can power analytics in a fundamentally different way. Retrieval-augmented generation (RAG) is generating a lot of buzz right now for all it can enable, but vector embeddings are what make RAG useful. They are a central component of the framework that helps with context, responses, integration of retrieval and fine-tuning of models. Generating high-quality vectors and querying them correctly is a critical task that enables any RAG system to actually work. There are other frameworks, but RAG is particularly well-suited for a first-party data revolution. Sounds great. Let’s all figure out how to use vectors and vector embeddings. This is not the total answer. The issues like limited data sets and tooling remain. All is not yet wrapped up in a pretty bow, but I believe it soon will be. Because open-source, pre-trained foundation models like Meta’s Llama 2, which will give way to the more robust Llama 3 in July, can level the playing field. The issue of not having enough data volume compared to BigTech gets mitigated. By using an open source model pre-trained on large and diverse datasets, that model has a certain level of knowledge and understanding built in. Companies simply need to fine-tune Llama 2 (or Llama 3) on their specific domain or task with their data. This eases the bottleneck because in many cases, you no longer have to train a model from scratch. This may sound like an oversimplification, given that Llama helps companies deal with text, but most of the data companies run on is not text. The structured data companies run on need to be integrated into this process. For example, the user behavioural events which form a large percentage of first-party data typically, are not suitable to be processed by any LLM. This is changing so companies should be ready as new multimodal solutions emerge. Similarly, tooling is still lacking, but there is a lot of attention on the space, so great strides are being taken. It’s coming along! With the biggest issues fundamentally addressed, first-party data hype is back, baby! Companies don’t have to worry about third parties violating privacy, nor do they have to depend on Big Tech to help them know their customers. Expect to see first-party data explode this year as companies finally take full advantage– especially with Llama 3 at the ready. For all of its promise, perhaps the greatest potential for Llama 3 will be to actually solve the first-party data problem once and for all. First-Party Data is Back … With a Little Help From Its Friends. How Vectors, RAG and LLAMA 3 Are Driving a Sea Change First-Party Data is Back … With a Little Help From Its Friends. How Vectors, RAG and LLAMA 3 Are Driving a Sea Change Over the last five years, the dominant narrative surrounding data infrastructure has emphasized the importance of companies owning and leveraging their data as they acquire as much information about their users and customers as possible. Due to mounting privacy regulations, they need to gather the data themselves instead of relying on third-party data operators, such as ad networks or platforms like Google, Meta , and Amazon . Companies have fallen in line with this narrative and made the shift. Google, Meta Amazon But, in the battle for the best data, is first-party really better? Not by itself, but it could be with a little help from vectors, frameworks like RAG, and open-source foundation models like Llama 3 . Llama 3 The Push for First-Party Data The argument for first-party data generally goes like this: companies need to become better stewards of data acquisition and management amid growing calls for data privacy . Consumers increasingly want to know who is hanging onto their personal information, how they got it, why they have it, and what is being done with it– and they generally don’t like the answers to those questions. Access and Delete requests are rapidly increasing, and the data privacy landscape is changing quickly. Companies are finding it hard enough to figure out their own privacy management processes; they don’t want to have to worry about third parties' as well. first-party data data privacy Access Access Delete Delete But the shift to first-party is not all about privacy. There is also the notion that third-party data will lose value as we move towards the proverbial cookieless future. Companies can’t get the same granular details they once could so why should they devote budget to a service that delivers less than it used to? And then there is the perpetual concern that the big platforms and ad networks will make unexpected changes. For example, they could change their algorithms, restrict access to certain types of data, or alter advertising policies in a manner that could harm a business’ performance with little or no notice. Being dependent on another company’s practices leaves one vulnerable. Companies feel stuck because they’ve already invested so much time, money, and resources into their data strategy. In this light, the push to take back control of data seems essential. But is it practical? The First-Data Problems No One is Talking About Early results for companies taking a gamble on first-party data have not met expectations. We’re seeing case after case of consumer companies that made the shift suffering. Farfetch , Allbirds , and SmileDirectClub are just a few examples. Would better, more strategic use of first-party data turn the tide on the rising customer acquisition costs? Farfetch Farfetch Allbirds Allbirds SmileDirectClub SmileDirectClub Still, the current reliance on first-party data– and the practices to extract that data– is a commonality across several companies that are experiencing tougher times today. It’s noticeable enough to make analysts, VCs, and marketers themselves ask if they were wrong to prioritize first-party data. The downsides of first-party data, as it is currently acquired and leveraged, are often considered to be underestimating the disappearance of device IDs, changing IP addresses, consumer adoption of fake emails, and ad blockers. While true, much more significant issues are at play. First, there is a massive talent gap. Big Tech and the platform companies snag the best. They have the most to offer, making it difficult for up-and-coming consumer companies to compete for the data scientists and ML talent needed to make sense of the information being collected and analyzed. Without truly exceptional people, companies have struggled. There is also a real tooling problem. The offerings available to companies are nowhere near equivalent to the tools Big Tech companies boast internally (which can be a factor in the talent gap). Tooling makes a difference, and most companies simply can’t compete right now. Finally, there is a volume challenge. Big Tech and the ad networks have mountains of data, as these companies pool and anonymize hundreds of billions of data points to make their models run effectively. By contrast, if a company has only its data to work with, there is just not enough for ML to work as promised. While these problems seem serious, is it time to give up on the potential– and the need for– first-party data? No way! The Power of Vectors The biggest issue hindering first-party data is how companies are trying to access it. Up to this point, businesses have taken an Old World approach. Models must be built from scratch to extract the value from data that businesses require. This takes time, money, and most of all talent; it depends on how good your ML engineers and data scientists are. However, as discussed above, there is not enough available talent to make this approach work better than leveraging third-party data. The lack of talent creates the bottleneck. However, this does not mean we need to give up on first-party data. We just need to change how we approach it. In the New World that is possible today, vectors and vector embeddings are the key. Vectors are generic mathematical objects that can represent data points' features or attributes while embedding models analyze patterns in data to generate these information-packed, meaningful representations learned from data; they capture the semantic relationships. Vector embeddings are the format that can encode everything you know about a user or a customer and make that information accessible to an analytics system, or leverageable to personalize the user experience, or even to catch fraud. There are so many possibilities. Vectors are poised to drive a sea change because they can power analytics in a fundamentally different way. Retrieval-augmented generation (RAG) is generating a lot of buzz right now for all it can enable, but vector embeddings are what make RAG useful. They are a central component of the framework that helps with context, responses, integration of retrieval and fine-tuning of models. Generating high-quality vectors and querying them correctly is a critical task that enables any RAG system to actually work . There are other frameworks, but RAG is particularly well-suited for a first-party data revolution. to actually work Sounds great. Let’s all figure out how to use vectors and vector embeddings. This is not the total answer. The issues like limited data sets and tooling remain. All is not yet wrapped up in a pretty bow, but I believe it soon will be. Because open-source, pre-trained foundation models like Meta’s Llama 2, which will give way to the more robust Llama 3 in July, can level the playing field. The issue of not having enough data volume compared to BigTech gets mitigated. By using an open source model pre-trained on large and diverse datasets, that model has a certain level of knowledge and understanding built in. Companies simply need to fine-tune Llama 2 (or Llama 3) on their specific domain or task with their data. This eases the bottleneck because in many cases, you no longer have to train a model from scratch. This may sound like an oversimplification, given that Llama helps companies deal with text, but most of the data companies run on is not text. The structured data companies run on need to be integrated into this process. For example, the user behavioural events which form a large percentage of first-party data typically, are not suitable to be processed by any LLM. This is changing so companies should be ready as new multimodal solutions emerge. Similarly, tooling is still lacking, but there is a lot of attention on the space, so great strides are being taken. It’s coming along! With the biggest issues fundamentally addressed, first-party data hype is back, baby! Companies don’t have to worry about third parties violating privacy, nor do they have to depend on Big Tech to help them know their customers. Expect to see first-party data explode this year as companies finally take full advantage– especially with Llama 3 at the ready. For all of its promise, perhaps the greatest potential for Llama 3 will be to actually solve the first-party data problem once and for all.

How Vectors, RAG and Llama 3 Are Changing First-Party Data

কিভাবে ভেক্টর, রাগ এবং লামা 3 প্রথম পক্ষের ডেটা পরিবর্তন করছে

Wie Vectors, Rag und Llama 3 First-Party-Daten verändern

Cómo Vectors, Rag y Llama 3 están cambiando los datos propios

Comment Vectors, Rag et Llama 3 modifient les données propriétaires

वेक्टर्स, रैग और लामा 3 किस तरह से फर्स्ट-पार्टी डेटा को बदल रहे हैं

Vectors、Rag、Llama 3 がファーストパーティ データをどのように変えているのか

Vector, Rag 및 Llama 3가 자사 데이터를 어떻게 변화시키는가

Como Vectors, Rag e Llama 3 estão mudando os dados primários

Как Vectors, Rag и Llama 3 меняют собственные данные

Vektörler, Rag ve Llama 3 Birinci Taraf Verilerini Nasıl Değiştiriyor?

Cách Vectors, Rag và Llama 3 thay đổi dữ liệu của bên thứ nhất

Vectors、Rag 和 Llama 3 如何改变第一方数据

In 1890 the United States Congress nearly unanimously passed the Sherman Antitrust Act. Just 21 short years later, this law was used by the Supreme Court against Standard Oil, JD Rockefeller’s petroleum empire. The government accused Standard Oil, of creating secret deals with their partners, price discrimination and providing favorable treatment to certain businesses, among other things. This situation is not a thing of the past. Back then it was Standard Oil, but today it is occurring with another household name — Facebook. Facebook is no stranger to criticism, but its monopolistic behavior has recently come under public scrutiny once again. Since the Menlo Park giant acquired Instagram in 2012, it has held majority control of the social media advertising market, allowing it to profit richly from an almost exclusive and unchallenged monopoly. Across all its platforms, Facebook made over from advertising alone. This level of dominance in the market gives Facebook the ability to show favoritism towards billion dollar companies with deep pockets who spend heavily on their platform while strong-arming smaller, local competitors and stifling entire industries. $55 billion in 2018 One powerful example of this involves Smile Direct Club, a three billion dollar company with a massive in-house . marketing department of 125 people Smile Direct Club is a social marketing behemoth, with over 1,100 Facebook ads live in the United States and over 100 in Canada — undoubtedly making them one of Facebook’s largest advertisers. Their massive budget allows them to reach tens of millions of consumers each day. Their ads attract more consumer attention on social media — in the form of likes, shares and social buzz — than much larger household multi-national brands. However, a large advertising budget, while notable, is nothing newsworthy. The real story here is the type of ads Smile Direct Club is able to run on the Facebook platform. These ads do not follow the regular rules and regulations that the rest of Facebook’s advertisers are held to. In fact, many of their ads are in direct and blatant violation of the rules Facebook has created for the public good. How is this the case after all the to protect Facebook users? It’s easy enough to see for yourself. Following criticism over Russian interference in the 2016 presidential election and the lack of transparency surrounding ads on its platform, Facebook responded to numerous Senators’ concerns by releasing the — a publicly accessible tool that allows anyone to view the ads any company runs on Facebook. promises Mark Zuckerberg made to Congress Facebook Ad Library Looking through , one consistently sees ads that show before and after smile shots, zoomed in simulations of moving teeth, close-ups on only a portion of the face highlighting the person’s teeth and lips, and questionable unsupported claims about medical efficacy. Smile Direct Club’s ads One can also see ad copy that makes direct claims about how their treatment will result in improvements in a person’s confidence, smile and even instructs the viewer to fix their ‘snaggle tooth’. Each of these is a clear violation of , specifically those pertaining to . Facebook’s Advertising Policies Section 4.19 on Personal Health Yet Smile Direct Club has hundreds of these kinds of ads running every month. t. Section 4.19 prohibits ads about personal health that show “before-and-after” images or “ad images focusing on zoomed body parts” and Section 4.12 of Facebook’s ad policies prohibit ads that assert or imply things about individuals’ “personal attributes” and explicitly lists physical health as part of tha Facebook even gives examples of ads that are compliant and not compliant to make it clear to advertisers what is and is not allowed on the platform. Yet when you compare many of Facebook’s examples to what Smile Direct Club is actually advertising, it becomes apparent Facebook is not enforcing their own rules. What’s worse is that not only is Facebook allowing a company to blatantly run almost a thousand ads across numerous continents that are in direct violation of its ad policies, . it is also preventing Smile Direct Club’s competitors — dozens of small local orthodontists — from running similar ads After speaking with numerous orthodontists in both Canada and the US, we have learned that massive discrimination is taking place with advertising on Facebook. After public trust was already rocked with allegations of election interference through Facebook, this is sadly not shocking. It is affecting thousands of small business owners which make up the heart of the American economy. These orthodontists assert that they have had almost all of their ads denied by Facebook over the last several months. Facebook cites their ad policy — Section 4.19 — as the reason for the denial, yet that very same ad policy does not seem to apply to Smile Direct Club. What’s worse is that many of these orthodontists have appealed the decision, citing Smile Direct Club ads, yet the orthodontists’ receive auto-generated responses while their ads continue to be denied. Wanting to investigate this further, . We looked at active ads from Smile Direct Club and designed ours to have the same visuals and make the same claims. Every single ad we tried was denied by Facebook . We received various feedback including: we designed a number of ads explicitly modelled off those that Smile Direct Club was running “This ad isn’t running because it uses images that excessively focus on a person’s body or body part.” “This ad can’t use images that focus on a person’s body or body part, or depict unlikely before-and-after results.” “Ads referring to someone’s body or appearance are personal in nature are not prohibited and we don’t want users to feel singled out” “It looks like the business model/product or service being promoted through your ad is against Facebook’s Advertising Policies.” Each and every one of these comments would also be applicable to the Smile Direct Ads. Hilariously enough, the very same ads sponsored by Smile Direct Club appear in our very own News Feed to this day. Advertising for any small business is difficult enough, but recently Facebook has, by all appearances, made it nearly impossible for orthodontists to have a presence on their platform by discriminating against small businesses in favor of their larger competitors with deeper pockets, arbitrarily blocking ads and shouting out the little guy’s voice. So while it is difficult to find quantifiable ‘proof’ that Facebook has been discriminating against smaller advertisers — just like it would have been difficult to prove that they were or — exposing confidential user information to a political consulting firm allowing Russian trolls to interfere in US elections if we consider the repeated experiences of these orthodontists all over North America and our own personal experiences in failing to have our own ads similar to those of Smile Direct Club published, it is hard to see how anything but this is occurring. What’s worse is that not only does Facebook appear to be showing favoritism and arbitrarily applying their advertising standards, they are also ignoring the prevailing medical opinion while doing so. The American Association of Orthodontists and The American Dental Association have time and again warned about citing the high number of cases gone wrong, some with irreparable damage. the dangers of do-it-yourself orthodontics Attorneys general in have received from the AAO. Dental boards in Alaska, California, and West Virginia have into the as well. 36 states complaints against Smile Direct Club opened investigations company’s practices So, Facebook is essentially saying that professionally licensed and regulated in-office orthodontic treatment offers “unlikely before and after results” of a properly aligned smile, but that same consumer can achieve a more likely result with a few aligners received in the mail from Smile Direct Club after taking pictures of their mouth. Meanwhile, others on Wall Street are taking notice. A story on cites a report that “SmileDirectClub is taking the startup approach of ‘moving fast and breaking things’,” analysts wrote. “In this case, unfortunately, they seem to be ‘breaking’ many of their customers’ teeth.” Business Insider Thus, it would appear profit is a more important corporate value to Facebook than protecting the health and wellbeing of its users. Facebook is using its monopoly over social media advertising to empower companies with deep pockets like Smile Direct Club, giving them special treatment while shutting out the little guy despite what dental professionals recommend. Even the co-founder of Facebook recently wrote remarking on Facebook’s monopolistic behavior, saying it is time to break it up. an op-ed for the New York Times This behavior is bad for consumers and competition alike. Just like in the days of Standard Oil, consumers are deprived of their right to a free market. They are not given a chance to see all their options and learn about the benefits of traditional orthodontic treatment. Facebook wants to present itself as a neutral platform for content and advertisers, but more and more this just does not seem to be the case. Facebook may or may not legally qualify as a monopoly — that is a question for the lawyers — but its behavior is manipulating the market against consumers’ best interests. Regardless of whether Congress decides to break up Facebook or not in the coming months this hypocrisy and discrimination must end. Zuckerberg’s behemoth cannot be allowed to continue promising equity and reform in public while discriminating and showing favoritism in private. Facebook and Mr. Zuckerberg must be held accountable for their actions.

How Facebook’s Discriminatory Advertising Stifles Entire Industries

The very nature of the internet has drastically changed the way startups try to reach their customers, with many e-commerce brands deciding to bypass traditional resellers entirely so they can have greater control over their customer experience. Customer resource management tools give website owners everything they need to fully track customer interactions, inventory levels and the status of their shipments so that everything operates efficiently and somewhat (if you’re good) autonomously. Best of all, selling directly to the customer results in higher profit margins by eliminating reseller expenses, and operating exclusively online helps avoid the associated with opening brick-and-mortar locations — though certain brick-and-mortar costs are replaced by associated advertising expenses, explored below. overhead costs But as DTC e-commerce has experienced a boom, shifting technology and rising competition are creating new challenges for would-be entrepreneurs. A few key strategies are essential for navigating this tricky space. Changing Customer Acquisition Costs A big player in the rise of DTC e-commerce has been the improved methods of customer acquisition offered by Google, Facebook and other digital channels. When of social media users use these platforms to research and discover products, it’s clear that there is vast potential for DTC brands. 54 percent Unfortunately, while the audience is there, various trends have resulted in rising customer acquisition costs across the board. Not only has Facebook’s organic page reach fallen dramatically (to not even really being relevant) in recent years, but the percentage of digital audiences that see a DTC brand’s social content also declines as the audience grows. Top DTC brands are spending massive amounts of money in an effort to gain new customers. A report from MediaRadar that from Q1 2018 to Q2 2019, Peloton Interactive spent $180 million, while SmileDirectClub spent well over $200 million on both digital and traditional media channels. revealed As acquisition costs increase, DTC brands are becoming increasingly hard-pressed to gain new customers at a profitable level. Even worse, they may hemorrhage cash to acquire new users, with the hope that their customer lifetime value (CLV) will be roughly three times greater than that acquisition cost. The main problem with that? CLV is often hard to predict — and is usually lower than what’s estimated. The Value of Additional Channels With customer acquisition costs rising across the DTC space, many founders are finding that they cannot rely on the same channels they’ve always used if they wish to continue acquiring new customers. In fact, at the 2019 Modern Retail Summit, industry leaders that companies aiming to scale on a major level must also begin considering strategies for Amazon or getting their product on the shelves at Walmart. In other words, major sustained growth will likely require a step away from a pure DTC model. noted DTC combined with traditional retail is traditionally being seen as the best long-term approach for venture capital-funded brands. Another important consideration for DTC businesses is going beyond the common trifecta of Facebook, Google and Instagram to find new channels for reaching your target audience. Conducting additional research on your target audience and the channels they use can easily reveal more cost-effective platforms for growth. Improve Data Usage As a largely digital platform, it should come as no surprise that managing your data is key to success in the DTC sphere. There are seemingly countless data points to track the customer’s journey, particularly as you further diversify the channels you use to reach them. Ideally, you should be able to track a customer’s initial encounter with your brand, past purchase behaviors and even how they browse your website. Digging deep into the numbers will allow you to see which channels deliver prospects most likely to make a purchase. Diving into your cart abandonment rates could help you optimize your checkout process to reduce sales losses. Better understanding can help you improve keyword usage on your site. search intent This information is readily available through Google, your web hosting platform and even the social media tools you use to drive new traffic. The problem, of course, is that many DTC brands and other startups fail to use the data they have — even though it can offer a competitive edge by helping you identify your highest-converting products and sales channels. by Nikolay Savin for DATAVERSITY, AI tools and big data can improve all aspects of DTC retail: “AI-powered price analytics solutions consider all the pricing and non-pricing parameters such as seasonality, weather, customer behavior, and business goals.” As noted Continued Savin, “Moreover, such solutions establish latent interconnections between the variables, help to group products into clusters depending on their sales potential and suggest pricing moves by weeks earlier than in a traditional scenario. […] With AI-based technology, over 90 percent of products can be sold when necessary, while revenue and sales can grow by 10 percent and 15 percent respectively.” Channel Optimization Using data and channel research, channel optimization will prove key for successful DTC scalability. You need to consider how your own website can work in conjunction with other retail channels to get more product to your customers. As Daniel Backhaus of Core dna explains, is key for your overall growth. “Identify which products are performing really well with your retail partners, and which ones aren’t. Since online retailers are the most significant source of revenue for most brands, you don’t want to draw sales and traffic away from those products that are performing well as it would be counterproductive. Instead, with careful inventory planning, you can focus your strategy on those products that don’t perform well at your retail partners.” avoiding channel conflict Your DTC platform can prove most successful when it prioritizes products that don’t perform as well with other retail channels. A similar approach can work with the marketing platforms you use. Certain products may see more successful marketing results when targeted to a particular channel. As with any major business activity, continually testing and tracking results will prove essential for determining which channels and marketing platforms prove the most effective for shifting inventory. Changing tech and even global events like the coronavirus can impact everything from product manufacturing to which channels are best for acquiring new customers. DTC e-commerce founders must take a proactive approach and consider the opportunities and threats to their . growth By fully evaluating all your options, you will be better equipped to take advantage of this continually shifting marketplace so you can rise above the competition.

Technology Has Led to the Boom of DTC E-Commerce; Here’s How to Take Advantage

When considering where to launch their startup, many entrepreneurs naturally think of the “Innovation Hubs” of Boston, the San Francisco Bay Area, and New York City. After all, that is where the deals are, right? Well, they’re not the only places where companies are being launched and receiving game-changing investments. Each year, our firm publishes The State of Startups (SM) in the Southeast report which delivers a comprehensive overview of the venture capital and startup ecosystem in the southeastern United States. This year’s report once again shows the Southeast to be an attractive place to invest in startups relative to the more established and capital-intensive Innovation Hubs. Furthermore, our 2019 report reveals that the overall rate of maturation of the venture ecosystem in the Southeast is exceeding that of the Innovation Hubs, with more dollars than ever being invested in early and growth-stage southeastern companies. While most large and established growth equity funds are already investing in the region, we’re also seeing more capital being deployed by Southeast-based investors. In 2018, 25 percent of the top five most active VCs in each of the nine southeastern states the report examined were from the Innovation Hubs. In this year’s report, that number has fallen to 18 percent. Local funds are getting larger and, therefore, have a bigger market presence in the region. Regardless, if your company is successful, venture capital abounds. In fact, the aggregate revenue multiple for deals done in the Southeast since 2014 has grown 40 percent over the same analysis done last year. But access to funding isn’t the only reason why the Southeast is a great place to start a business: No matter how innovative your product or service is, companies must attract and retain top talent to be successful. Strong university systems that can provide the human resources your startup needs are located throughout the Southeast, from the University of North Carolina and Vanderbilt University to the University of South Carolina, Georgia Tech, the University of Georgia and many, many more. Ready Talent Pool. The Southeast offers a , especially when compared with large cities in the northeast and California. This is true not only as it relates to housing, goods, and taxes, but also for the cost of doing business as well. The Southeast tends to offer greater affordability in terms of commercial real estate leasing and the cost of acquiring talent, for instance. Located in Atlanta, Hartsfield-Jackson International Airport is a global gateway offering nonstop service to more than 150 domestic and 70 international destinations, including major commercial centers in Europe, Asia, and South and Central America. Even if your business isn’t located in Atlanta, you can still drive there from many other southeastern cities in just a few hours to catch a direct business flight. A lot of things are required for fostering new businesses, including factors we’ve already discussed like access to talent and the availability of capital. Research universities, such as those in the Research Triangle, technology incubators, and accelerators are also important contributors to a vibrant startup ecosystem. The Atlanta Technology Development Center at Georgia Tech is a good example of the latter, although robust ones exist in most all of the nine southeastern states our report examined. Lower Cost of Living. lower cost of living Easy Access to Anywhere. Vibrant Ecosystem. Other contributing factors include startup-friendly civic and state governments which often provide free marketing assistance, help entrepreneurs make connections, and offer tax breaks. These things are harder to get in the more established Innovation Hubs where there are so many businesses being built. Lots of Fortune 500 corporations were “born and raised” in the Southeast—think The Home Depot, Delta Airlines, The Coca-Cola Company, UPS, FedEx, and more. The region also has its share of “unicorns,” which are privately-owned companies that have reached a valuation of $1 billion or greater, including such names as Epic Games, JetSmarter, Magic Leap, SmileDirectClub, and others. You’ll Be in Good Company. It’s clear the Southeast is increasingly being recognized as a great environment for entrepreneurs in the early stages of building a business. The bottom line: Don’t overlook the region. Overall, 8,383 investments totaling $28 billion have been made in southeastern startups since 2014. For more information on the region’s startup scene,especially as it relates to venture funding, read our 2019 The State of Startups(SM) in the Southeast report. The report is free and can be accessed . here BIP Capital. The State of Startups(SM) in the Southeast. October 2, 2019. Statistics Source: To listen to the on The State of Startups(SM) in the Southeast for 2019 with Mark Flickinger, visit: https://youtu.be/LlZghFoknc0 podcast About the Author: Mark Flickinger is COO of BIP Capital , a venture capital firm that takes a partner approach with its investments by providing both operational and strategic direction to help promising early-stage businesses accelerate farther and faster. By providing financial, operational, and other resources, the firm equips its portfolio companies to achieve and stay on a glide path of growth. Flickinger holds a bachelor’s degree from Princeton University, and earned an MBA from the University of North Carolina’s Kenan-Flagler Business School. Starting as an undergraduate, he spent a decade competing as a member of the U.S. National Rowing Team. Flickinger has served on numerous boards at entrepreneurial companies and also works in a key partner role at BIP Capital with a focus on post-investment talent acquisition and operational management. Connect with him on LinkedIn and follow him on Twitter @BIPCapital .

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