How to get the most out of your CDP: 8 CDP use cases for driving customer loyalty through marketing
Let’s say your marketing team wants to run a win-back campaign to rescue at-risk customers before they churn.
Easy enough, right?
Not necessarily. If your tech stack is like a lot of ecommerce brands’, you’ll have to:
- Manually export data from your marketing tool via static CSV.
- Import that CSV into your analytics platform.
- Run an RFM analysis in your analytics platform.
- Export audiences from your analytics platform into a CSV.
- Manually import that CSV as a list into your marketing tool.
- Create a list of each RFM group in your marketing tool.
- Use RFM lists in one-time marketing campaigns (which immediately become outdated).
- Repeat every month.
This process is not only cumbersome and time-consuming. It also requires your marketing team to manage multiple integrations, develop expertise in 3 different systems, and guess at whether your marketing platform is effectively leveraging the insights from your other systems.
Besides, if you’re like most marketers, you’re dealing with far more than 3 systems in your tech stack.
Olivia Yuan, co-founder of Shopify-focused agency Tomorrow, says her agency’s clients use, on average, 30-50 third-party applications to power their ecommerce experience—and while most of those systems have their own data structures and attribution models, “many of them have overlapping features and functionalities,” she points out.
What if, instead, you could eliminate most of those steps above—by using one platform?
“It’s great if a CDP can unify all your data in a single place, and make that data accessible in other platforms,” says Nick Kobayashi, group product manager at Klaviyo. “But if you can’t analyse and act on that same data under the same roof, you’re missing a big chunk of value.”
Here, we discuss 8 CDP use cases that defy categorisation—and ultimately make your marketing work not only harder, but also smarter. (Note: Not every CDP supports all of the following use cases; Klaviyo CDP does.)
1. Sharpen segmentation with data transformation
What it is
Data transformation is when a CDP allows you to change the structure, formatting, and values of your data so you can operationalise them more effectively.
Why it matters
“As your data matures and you add more pieces to your tech stack, those data sources often have different formats for profile properties, events, and metrics that mean the same thing,” points out Anthony DelPizzo, lead product marketing manager, Klaviyo CDP—for example, “birthday,” “birth date,” “date of birth,” and “DOB.”
Without data transformation, “if you wanted to run a segment based on everyone who’s born in April, you’d have to do all these workarounds to account for those formatting differences,” DelPizzo explains.
Or, “if you wanted to build a localised segment, you would need to know every single synonym for that state or country,” says Tony Morelli, director of product design at Klaviyo. “You would need to understand all of these other pieces to make it happen.”
The result: “You’d miss a lot of people, your segmentation wouldn’t be as effective, and your reporting wouldn ’t be accurate,” DelPizzo says.
Data transformation eliminates the need for complicated “if” statements in template blocks, as well as long sets of filters in segments and flows—giving you more confidence in the data you use to power segments and marketing automations.
A good CDP recognises, “OK, all of this data means the same thing, so let’s clean that up and standardise it,” DelPizzo says. “That means not only backfilling all historical data, but then also, upon ingestion, recognising that data point and automatically transforming it. You set up these rules once, the CDP runs it automatically, and you can be confident that your data is clean.”
How to use these CDP insights to enhance your marketing
- Standardise location values: Across data sources, profile properties might use different values for the same item—“Canada,” “CAN,” and “CDN” for the country property, for example. Standardise all values to pull an accurate list of customers located in Canada.
- Improve data hygiene: If data was erroneously uploaded with quotation marks or extra surrounding spaces, for example, remove those. Or, capitalise all first and last names via title case capitalisation transformation.
2. Achieve a 360-degree customer view with data warehouse syncing
What it is
Data warehouse syncing is when a CDP pushes event and profile data in batch to third-party data warehouse destinations, or to an S3 bucket, at an established cadence.
Why it matters
Since it allows you to avoid setting up costly and complex custom integrations, data warehouse syncing saves you money and time, makes your data more consistent across your organisation, and gives you more control over the customer data your CDP sends downstream.
Not every company that needs a CDP needs data warehouse syncing, Morelli acknowledges. But when a CDP offers it as an option, it’s evidence of a philosophy that’s “an important distinction in the CDP world,” Morelli says: “Put your data wherever you need your data. We will house it, we will keep it normal, we will keep it safe. But if you want it elsewhere, we’re not going to hoard it.”
Along with anonymous backfill and data transformation, Flavia D’Urso, lead product designer at Klaviyo, says data warehouse syncing represents a “big value add” of using a CDP: “being able to clean your data and make rules around it, and then have it do exactly what you want.”
How to use these CDP insights to enhance your marketing
- Send profile data from CDP to data warehouse: Combine CDP data with data from other platforms to generate a 360-degree view of the customer in your data warehouse, powering data consistency for accurate analysis and better customer experiences across your organisation.
- Execute data visualisation with connectors to business intelligence tools: Report on and visualise CDP data from a centralised place for multiple data sources—without having to log in.
- Store data for disaster recovery: Keep a back-up of all data in an external warehouse in case of disaster or acquisition.
3. Optimise customer engagement with webhooks
What it is
Webhooks refers to a CDP’s real-time data export of event data via webhooks, including key webhook topics like channel subscription changes.
Why it matters
Using webhooks synchronises your data across your marketing technology stack, streamlines time to value and marketing automation, and gives you more confidence and trust in your data.
How to use these CDP insights to enhance your marketing
- Sync when a customer unsubscribes from email to other systems: Send unsubscribe data to systems of engagement to ensure customers who have opted out don’t receive communications.
- Sync channel engagement data to analytics tools: Send engagement data, such as opens and clicks, to systems of insight to enhance customer analysis.
4. Identify up-sell opportunities with audience performance reporting
What it is
Audience performance reporting is a CDP analytics tool that allows you to compare the performance of different audience segments.
Why it matters
By eliminating the need to export data into spreadsheets or use a separate ecommerce analytics tool, audience performance reporting saves you time, improves analysis, and gives you a better understanding of your target audiences.
How to use these CDP insights to enhance your marketing
- Compare channel performance by segment: Identify top-converting SMS vs. email segments by comparing segment-specific conversion metrics across each channel.
- Isolate the customer archetype responsible for negative trends: Compare metrics like average order value (AOV) across top segments to identify the segments with the lowest AOV and determine which areas to test, optimise, or up-sell.
5. Prevent customer drop-off with funnel analysis
What it is
Funnel analysis is a customisable CDP dashboard for analysing the customer journey.
Why it matters
By uncovering potential optimisation opportunities faster, funnel analysis speeds up time to value, improves personalisation initiatives, decreases drop-off, and boosts conversion rates.
Klaviyo CDP’s funnel analysis, for example, is one of Morelli’s favourite features. “Never before have I been able to understand all of my customer touchpoints and my drop-off and how it’s changing point to point,” they explain.
How to use these CDP insights to enhance your marketing
- Enhance messaging in your welcome series by identifying areas of drop-off from welcome series to purchase funnel: Adjust messaging or email design to include discounts and/or product recommendations based on a customer dropping off after a step in your welcome series to purchase funnel (i.e. receives an email, clicks an email, active on site, adds an item to cart, places an order).
- Test channels by switching to SMS or push: Optimise your cross-channel marketing strategy by testing another channel when sending an email results in a dip in the funnel.
6. Enhance personalisation with custom CLTV
What it is
Custom CLTV is a CDP feature that empowers you to customise your predicted CLTV, which represents a person’s value to your company over their entire lifespan as a customer.
Why it matters
CLTV customisation leads to improvements in segmentation and personalisation, as well as more accurate forecasting around CLTV.
How to use these CDP insights to enhance your marketing
- Pull a segment of top predicted BFCM customers: Many customers only purchase during BFCM. Customise CLTV specific to the upcoming 90 days (BFCM timeframe) in order to predict your best customers during BFCM specifically, rather than your best customers for the entire year.
- Cross- and up-sell to customers who are likely to buy soon: Send a discount to customers who have bought 2+ items and are likely to buy soon, using products they have viewed or which complement their previous purchases.
7. Reduce customer churn with RFM analysis
What it is
RFM analysis, or recency, frequency, and monetary analysis, refers to the grouping of customers based on their purchase behaviour —specifically, how recently they made a purchase, how frequently they purchase, and how much they spend.
Why it matters
Especially when a CDP incorporates RFM analysis out of the box and integrates it seamlessly with digital marketing channels, RFM analysis saves you time, improves segmentation and personalisation, and reduces total cost of ownership by eliminating the need for a separate RFM tool.
Klaviyo CDP’s RFM feature, for example, “is really exciting in that we’re basically modelling your data based on someone’s purchase activity, and then profiling them based on whether they’re a champion customer or inactive or at risk,” Kobayashi says.
Sure, you could build a segment of “at-risk” customers manually. “But usually what that means is you’re just guessing at whatever you think those conditions might be,” Kobayashi points out. “You’re guessing that ‘at risk’ means someone hasn’t purchased in 90 days, for example. And that might be a short-sighted definition.”
By contrast, “with RFM, you’re using an intelligent model to dictate the definition,” Kobayashi explains. “The predictive model is actually looking at the data and determining which specific thresholds constitute an at-risk customer vs. a champion customer.”
“It removes the subjectiveness,” Kobayashi adds, “as well as the need to define every single condition in order to infer whether someone’s at risk.”
How to use these CDP insights to enhance your marketing
- Create “needs attention” and “at-risk” segments in seconds and send them each a targeted win-back campaign: To maximise retention, offer a discount to customers at risk of churning, and personalise messaging to formerly high-value customers who haven’t purchased in a while.
- Identify opportunities to mitigate churn risk: Analyse the impact of the previous season’s marketing activities on purchase behaviour and customer retention in order to understand what different audiences respond to, then increase spend in those areas.
- Push champion segments to Facebook Ads and Google Ads: Retarget or create a lookalike audience based on top-performing segments.
8. Improve audience targeting with anonymous visitor activity backfill
What it is
Anonymous visitor activity backfill is when a CDP tracks anonymous browsing activity on-site, stored locally on the browser, and then matches it with known customer profile data once the visitor takes an action to become identified (fills out a form, clicks an email, places an order, etc.).
Why it matters
Anonymous visitor activity backfill allows you to enrich customer profiles with historical data and gain a more robust view of your customers’ engagement with your brand, translating to better segmentation and personalisation at scale.
How to use these CDP insights to enhance your marketing
- Target window shoppers: Create a segment of people whose profiles were created yesterday, and who viewed 10+ products previously.
- Enhance product recommendations to convert first-time customers again: Send product recommendations to a shopper who viewed 5 different items before adding one to their cart and purchasing it, or offer them a discount for a highly targeted cross-sell marketing campaign.
Your CDP must fit the needs of your marketing strategy
A lot of CDPs claim they’re for marketers, “but they’re not actually marketer-friendly,” DelPizzo cautions. “They’re really hard to use, meaning not only that it takes a lot of time to get things done, but also that it’s super complex to make any changes, and it requires tons of additional resourcing or additional learning.”
Even if marketing “owns” the CDP, then, “to really see value and use it to its fullest, marketing often needs to lean on other teams,” DelPizzo explains.
With a user-friendly CDP like Klaviyo CDP, DelPizzo says, use cases often involve “a 1 + 1 = 3 motion that we want people to get familiar with. It’s not that you can’t do some of this with other CDPs, but often it’s a much more cumbersome process, and you still have to send that data downstream to your marketing tool.”
With data collection, data storage, data transformation, marketing activation and orchestration, and customer insight analysis all under the same umbrella, “Klaviyo CDP makes sure that as the data’s arriving, we’re also making it very purposeful for all the different ways it’s going to be used,” Kobayashi explains.
Whether that’s for sophisticated segmentation, marketing automations, real-time reporting, or something else, Kobayashi adds, “our platform automatically manages the complexity of how that data needs to be shaped in order to support marketers.”
CDP use cases FAQs
How does a CDP differ from a data management platform (DMP)?
DMPs are primarily used in advertising. They focus on anonymised, third-party, cookie-based data which they store temporarily. CDPs, by contrast, are primarily used for marketing across the entire customer journey. They focus on zero- and first-party data: information your subscribers and customers hand over voluntarily, and information based on observing customer behaviour on your website and owned channels. A good CDP also stores your data for as long as you want.
What types of data can be stored in a CDP for marketing?
While a CDP ingests data from anywhere, it’s focused primarily on zero- and first-party data, or data you collect ethically and consensually from your customers. This may include behavioural data, such as information about actions someone has taken on your website or app; transactional data, such as information about someone’s past purchases or returns; and demographic data, such as someone’s name, location, and age.
Can a CDP integrate with other marketing tools and platforms?
Yes—integration is a big part of a CDP’s job. A CDP collects, unifies, and stores customer data from multiple sources at scale, and makes it available for manipulation and distribution to systems of insight and engagement. “Systems of engagement” includes tech like your marketing automation platform. Depending on the CDP, these systems may be native or external (bonus points when they’re native).