Customer Retention Analytics — Benefits
There are countless ways competitors might latch onto your loyal customers. But, smart marketers know how to engage and retain customers.
With customer retention analytics marketers track customer visits and decode purchase patterns. They anticipate shopping behaviors and engage customers with relevant offers.
Customers realize the value of (their) data and expect brands to do something smart with it. Without it, they will not engage; or will disengage abruptly, and often permanently. — Relevant Dialogue, Oct 2015
With customer retention analytics marketers entice customers with offers they care about. These offers not only tempt customers to make that next purchase, they add a feeling of special treatment customers expect. Marketers engage customers at unexpected times, or reward loyalty with promotions that complement items purchased, encouraging continued purchases.
“Sustained lift” is when a customer permanently changes their level of engagement after participating in your loyalty program. After a customer is incentivized to purchase a specific brand by receiving a reward, they might spend a greater share of overall wallet on that brand going forward –– often over a long period of time. — Colloquy, Dec 2017
Customer Retention Analytics — Challenges
Customer retention analytics are straight forward. The details are available in the sales data and can be tailored to unique customer segments or even individuals. The data management and data mining, however, are demanding and require deep dives into transaction data and complex joins with customer and product data.
Moreover, both the volume and velocity of data overwhelm Marketers. Many aren’t even sure of the data they have. They don’t believe they have the data they need; and much of what they have, they question the quality. Or they can’t access.
If retailers are collecting everything there possibly is to know about consumers, the things that are important in driving purchases will get drowned out by noise. The more they gather, the harder it is to separate the signal from the noise. — Forbes, Oct 2015
The roadblock isn’t statistics, but efforts spent to integrate data into actionable analytical data sets. Many business analysts might be Excel wizards, but lack data management skills. They aren’t trained in deep-dive analytics and they can’t manage complex data structures. So analysts create error-filled or incomplete analytics. And marketing executives lose confidence in both reporting and data.
Customer Retention Analytics — IDP
At IDP, we remove the requirement that business analysts manage large data volumes or complex data structures. Bridging the gap between data management and analytics. So analysts focus, not on data, but on making recommendations from analytics.
At IDP, we manage large data volumes with complex structures and we integrate disparate data sources. We build rock-solid analytical data sets targeted to specific marketing strategies.
And we always collaborate with marketers to generate analytics that produce marketable results.