There are countless ways competitors might lure your loyal customers. And that’s why savvy marketers use customer retention analytics to anticipate behaviors, engage customers, reward loyalty and retain loyal customers longer. The most successful weapon to fight customer attrition is creating a personalized customer experience unique to individual customers.
Retention measures the frequency a customer continues to do business with you, while loyalty measures their predisposition to select your business. When you attract a customer for a second time, she has been retained, but the reason isn’t due to loyalty. Your ultimate goal is to drive retention while making customers loyal to your brand. — Business2Community, Feb 2018
Customer Retention Analytics — Benefits
A core task in effective analytics is integrating in-house data on customers with external data gathered across multiple channels. From this data, unique customer traits and behaviors can be identified … having all of this customer analytics available on demand makes it possible to anticipate expectations — TechTarget, Jan 2017
With customer retention analytics marketers follow customers and track their purchases. They anticipate behaviors and engage customers with meaningful offers. If a loyal customer hasn’t visited when expected, marketers tempt the individual with an offer she can’t refuse.
Successful loyalty programs are built on data-driven customer insights… treat consumers who are most valuable differently. — TargetMarketing, Nov 2015
Customer retention analytics empower marketers to engage customers with offers they care about. These offers not only tempt, but also add the feeling of special treatment customers expect. Savvy marketers also reward loyalty with promotions on items that complement items purchased, encouraging extra purchases.
Customer Retention Analytics — Challenges
Even if CMOs recognize that they need to build stronger relationships with consumers through data analytics, many still struggle sifting through the vast amounts of data, coming up with actionable insights and then implementing them. — IBM, Nov 2015
Customer retention analytics include: segmentation; market basket; and recency, frequency, monetary. The details are available in the sales data. And the analytics can be tailored to customer segments, or even individuals.
Another problem that marketers run into is that they don’t have the skillsets to understand and manage data, along with properly running tools to analyze and gather data. — Forbes, Oct 2015
Many analysts don’t engage in customer retention analytics because they lack data management or data mining skills. They can’t manage complex data. And they’re stymied by a limited toolset. So analysts build incomplete or error-filled analytics. Marketers don’t get the customer picture they need and lose confidence in both reporting and data.
Customer Retention Analytics — IDP
At IDP, we solve your complex analytics while facing limited resources. We remove the requirement that analysts manage complex data volumes. We bridge the gap between data management and analytics. Analysts focus, not on data, but on the analytics.
We manage large data volumes with complex structures. We integrate disparate data sources to build rock-solid analytical data sets. And we always collaborate with marketers to generate actionable results.