How to use your CDP for marketing

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.

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 organization, 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”: “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.”

• Send profile data from your CDP to a 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 organization.
• Orchestrate data visualization with connectors to business intelligence tools. Report on and visualize CDP data from a centralized 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.

Webhooks refers to a CDP’s real-time data export of event data via webhooks, including key webhook topics like channel subscription changes.

Using webhooks synchronizes your data across your marketing technology stack, streamlines time to value and marketing automation, and gives you more confidence and trust in your data.

• Sync when a customer unsubscribes from email to other systems. Send unsubscribe data to systems of engagement to make sure 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.

Audience performance reporting is a CDP analytics tool that allows you to compare the performance of different audience segments.

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.

• Compare channel performance by segment. Identify top-converting text messaging 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, optimize, or up-sell.

Funnel analysis is a customizable CDP dashboard for analyzing the customer journey.

By uncovering potential optimization opportunities faster, funnel analysis speeds up time to value, improves personalization initiatives, decreases drop-off, and boosts conversion rates.

Advanced KDP’s funnel analysis is one of Morelli’s favorite 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.

• 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 (e.g., receives an email, clicks an email, active on site, adds an item to cart, places an order).
• Test channels by switching to mobile. Optimize your cross-channel marketing strategy by testing another channel, like mobile push or WhatsApp, when sending an email results in a dip in the funnel.

Custom lifetime value (LTV) is a CDP feature that empowers you to customize your predicted LTV, which represents a person’s value to your company over their entire lifespan as a customer.

LTV customization leads to improvements in segmentation and personalization, as well as more accurate forecasting around LTV.

• Pull a segment of top predicted BFCM customers. Many customers only purchase during BFCM. Customize LTV 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.

RFM analysis, or recency, frequency, and monetary analysis, refers to the grouping of customers based on their purchase behavior—specifically, how recently they made a purchase, how frequently they purchase, and how much they spend.

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 personalization, and reduces total cost of ownership by eliminating the need for a separate RFM tool.

Advanced KDP’s RFM feature “is really exciting in that we’re basically modeling 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’s 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.”

• Create “needs attention” and “at-risk” segments in seconds and send them each a targeted win-back flow. To maximize retention, offer a discount to customers at risk of churning, and personalize messaging to formerly high-value customers who haven’t purchased in a while.
• Identify opportunities to mitigate churn risk. Analyze the impact of the previous season’s marketing activities on purchase behavior 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.

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 that identifies them (e.g., fills out a form, clicks an email, places an order, etc.).

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 personalization at scale.

• 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.

A CDP should do more than just unify profiles and segment audiences. It should also surface actionable insights while giving you the flexibility to transform and extend your data.

But with most CDPs, added capabilities come at the cost of complexity. “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,” cautions Fang.

Even when marketing owns the CDP, teams often rely on technical resources to unlock its full potential. A truly marketer-friendly CDP should provide advanced capabilities without bottlenecks.

With KDP, marketers get more than just data unification. They get a system designed for both power and simplicity. “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,” Fang explains.

By bringing data collection, data storage, data transformation, marketing activation and orchestration, and customer insight analysis into one vertically integrated platform, Klaviyo makes sure data is immediately usable for segmentation, automation, real-time reporting, and more.

As Kobayashi puts it, “our platform automatically manages the complexity of how that data needs to be shaped in order to support marketers.”

Do more with your data with Klaviyo. Get a demo