Hackernoon logoThe Impact of CDP in Marketing by@divyamulanjur

The Impact of CDP in Marketing

Divya Mulanjur Hacker Noon profile picture

@divyamulanjurDivya Mulanjur

Growth and lifecycle marketing consultant. Currently product marketing at Exponea.

CDP (customer data platform) is software that centralizes all your customer data and makes it available for any marketing campaigns. Centralized customer data gives you a complete and single point of view of all customer information and behavior. You can then activate this data by connecting the CDP to marketing platforms like email, Facebook, or SMS. Some CDPs come with native platforms for marketing activation and also have AI and machine learning folded into the mix to give you a one-stop solution for customer acquisition, conversion, and retention.

To understand the impact of CDP in marketing, and to gauge if it makes sense to add it to your martech, here are 6 key CDP features explained with real-world implementations.

Better Segmentation and Granular Targeting

Segmentation is a core feature of a lot of ESPs and CDPs that can be used to include or exclude audiences from campaigns. But not all segmentations are built the same. I'd like to illustrate this with two examples.

1. Let's say your marketing team is working on a discount campaign set to launch two weeks from now. To save ad $$ and to not agonize your customers, you want to exclude people who have purchased from you in the last two weeks and the two weeks prior to launching the campaign. You can do this by building a custom audience segment and excluding that segment from your campaign.

2. Segmentation using CDPs can get a lot more granular than that. For example, imagine that you're an online retailer planning to promote a clearance sale for a product category that only has a few sizes left in inventory. Sending a promotional email to everyone makes for bad customer experience. You don't want customers clicking to the website only to find their size not in stock. A CDP makes it possible to filter and segment based on product variants and metadata so you can promote the campaign only to people whose sizes are in stock.


Surrounding the Customer with Consistent Messaging

By now you know that it's vital to reach customers where they prefer to engage with you - whether that's email, social, or SMS. Your marketing organization might have separate teams for each channel, but to the consumer, you're the same brand everywhere. To provide a seamless experience and to make a more powerful impact, it is important that you surround the consumer with consistent messaging.

CDPs come with omnichannel journey builders so you can create campaigns that target audience segments on every marketing channel.

These journeys can be triggered on a particular date, or by customer action. You can then choose a target audience segment and reach them wherever they are present by promoting the same offer and/or content to all connected channels.


Here's a simple example of a post-purchase campaign for the hotel industry that involves email and SMS. After someone successfully books a room, the campaign checks if the customer is checking-in to the hotel the same day. If so, it sends an SMS from the concierge within 30 minutes of booking. If check-in is within the next 4 days, the customer is sent an email with cross-sell opportunities and an SMS from the concierge on the day of check-in. If the customer doesn't fall into either category, the campaign sends an email within 12 hours of booking, then an SMS three days before check-in, and finally an SMS on the day of check-in.


Improved 1:1 Personalization and Custom Recommendations

When I say personalization, I don't mean the #Firstname kinds. Personalization today has gone way beyond inserting customer data you have 'on file' into dynamic fields. We're all familiar with Netflix's 'Recommended For You' algorithm. Most CDP's come with a 'Product Recommendations' engine that offers the same thing for a brand. Basic versions of this engine can be rule-based and non-personalized - for example, recommending a list of best-sellers or newly added products. The most commonly seen personalization use case is product recommendations based on past customer actions.


But the more advanced versions utilize machine learning and AI to determine what someone is most likely to buy and the probability of purchase based on past interactions and recommendation models, to personalize content for each individual customer.

Here's an example of how I used personalization in email for a travel brand. The marketing team wanted to push the idea of weekend staycations in some of our key markets. To do this, we sent an email that would show best-selling hotels within a few miles of the user's location. So, based on where the email was opened, it displayed personalized recommendations for a staycation. See the full email here.


Real-Time Audience Syndication to Ad Platforms

Many of us have experienced this - you get an abandoned cart email and buy something from it. An hour later, you're on Facebook and you see an ad for the product you just bought. Not only is this annoying to a consumer (I, for one, have hit 'hide ad' a countless number of times), but it's also wasted ad money. The problem here is that marketing channels are working in silos. You have an ESP that doesn't communicate with the ad retargeting platform, so the product purchase status isn't updated in real-time.

A CDP functions with customer data at its core and unifies all marketing platforms (such as email, Facebook, Google). So when someone buys a product that was initially left in the cart, that information is updated in their profile and any audience segments that they're a part of. This information is then sent to all connected channels, and in this example, the customer is then excluded from retargeting. Some CDPs with marketing activation have super-fast data processing speeds, so are able to do this in real-time.

Using AI to Enrich Ad Retargeting Audiences

CDPs can identify high-intent prospects and quantify their likelihood of purchase using predictive analytics. This allows for interactions in the micro-moment, optimized ad spends, and higher-value lookalike audiences on Facebook. A simple example is illustrated below.


Achieving Efficiency and Scale Through Intelligent Automation

It might sound like complicated tech, but a lot of modern CDPs have been built with the end-user in mind. Personally, as a resource crunched marketer working in a startup, I loved that the CDP put power in the marketer's hands. I was no longer dependent on data scientists and engineers to pull reports and help me tie together fragmented data. But I wasn't spending countless hours figuring out a new platform or learning to code either.

CDPs help you scale and send more personalized campaigns at an improved cadence. When utilized fully, CDPs help marketing teams get more efficient by being the single point of truth for everything - customer data, segmentation, reporting, and much more.

I was first introduced to the world of CDP while on the hunt for an email marketing automation platform for a travel startup. At the time I thought I had found a 'really advanced email platform' and did not fully realize the potential of the gold mine I had stumbled onto. Implementing a CDP not only transformed our marketing efforts, but it also made me a better marketer. It was the tool I needed to push my limits and come up with new and inventive ways to reach customers and tell the brand story.

After a few good years of using a CDP with marketing activation to double our conversions, I was so convinced about the future of the tech that I decided to make the move from B2C to B2B and joined Exponea, one of the leaders in the CDP space. But if you're still not sure whether CDP is for you, I recommend this article on MarTech Today that outlines 9 questions to ask if you're thinking of a CDP. Plus, here's an easy and comprehensive checklist with more features you can expect in a CDP, to guide you through the CDP selection process.


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