Over 30 years ago, the airlines, with air mileage programs, and supermarkets, with targeted coupons, first leveraged loyalty marketing analytics. Retaining loyal customers with rewards is not new. Retention marketing and loyalty marketing analytics are not new. The strategy today is the same, but tactically, there’s no comparison. Data volumes, data complexities and data velocities have all increased rapidly. Consumers are more demanding. They expect personal and relevant offers. And the time marketers have to respond continues to drop.
Customers today want the best benefits 24/7/365 and they are willing to pay for them (as well as give up valuable data). Companies don’t create loyalty trends. Customers do. It’s the job of retailers to follow the trends and give customers what they demand. Loyal customers should get benefits every time they engage with your brand. And they should experience those benefits as soon as possible. — PaymentSource, Jan 2018
Loyalty Marketing Analytics — Benefits
With loyalty marketing analytics, marketers leverage data to get a panoramic view of customers. They track shopping behaviors and engage customers with relevant offers on items customers care about. Methods like segmentation, or recency, frequency, monetary (RFM) uncover powerful behavior patterns and define customer lifecycle profiles.
Customers want relevance… They 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
Loyalty Marketing Analytics — Challenges
Consumers are unforgiving of poorly targeted marketing. So more than ever, marketers depend on loyalty marketing analytics. And yet, marketers fail to get the analytics needed for targeted engagements. The challenge is effectively using all their collected data; and they’re drowning in data. Many aren’t sure of the data they have. They don’t believe they have the data they need; and what they have, they question the quality.
A problem marketers run into is that they don’t have the skillset to manage data, along with properly running tools to analyze data. With data, you’re able to identify a problem. But, you need to explain how you’re going to resolve that problem. — Forbes, Oct 2015
The roadblock isn’t statistics, but efforts spent integrating data into actionable analytical data sets. The data sets that generate analytics. In-house reporting tools can’t generate deep-dive data mining. And business analysts, who derive insights from data, can’t manage complex data. So marketers fail to get the insights needed. And lose confidence in both reporting and data.
Retention marketing and loyalty marketing analytics are not rocket science, but they are complex. Loyalty marketing analytics uses data from all available channels, learning as much as possible about customer behavior. Success depends on being able to generate meaningful interactions that tell a convincing story and can anticipate behaviors. Loyalty marketing analytics is a mix of at minimum 75% mining data for interactions and at maximum 25% analytics.
Loyalty Marketing Analytics — IDP
Your data is challenging and you have limited resources. IDP removes the requirement that business analysts manage unruly data — bridging the gap between data management and analytics. So analysts focus, not on data, but on making business recommendations from statistics.
We deliver actionable analytics, even when facing difficult data, that not only scale, but provide consistent, marketable results. With IDP, marketers control their marketing technologies!