Redefining Retail Loyalty with Big Data Analytics Solutions

Loyalty programs, in their entirety, can be a great driver for increasing sales and engaging consumers for a retail store or any business for that matter. These programs are not just a set of points or rewards accumulated by the buyer over time; they come with their own set of benefits as well. While the perks offered by such rewards may attract or engage consumers, they can have very little to nil contribution in fostering loyalty. How can marketers ensure that these rewards programs are effective engagement tools to connect or interact with their consumers? As marketers, are these retailers able to utilize the benefits of these programs fully? Are the brands focusing and featuring the right engagement models? What most organizations do not realize is that the effectiveness of such solutions depends on useful data sets focusing on building business-consumer lasting relationships.

The key here is that the ‘usefulness’ of the programs because most consumers, when signing up for such programs do not bother to offer personal information that is essentially correct.

Consider these numbers: According to Colloquy, in a US household, the average number of customer loyalty solutions memberships has risen by 21.9%, of which only 9.5% are active currently. Another study by Bond Brand Loyalty found that 60% of the millennial population would switch brands if a competitor offered better benefits.

The point to consider here: Although, the consumers may sign up for a lot of loyalty programs, they are not necessarily ‘engaged’ with the brand offering these programs. These set of customers merely enjoy the purchase and transactional benefits offered by the loyalty programs for customers, and if a competitor comes up with a better deal, they hardly have any qualms switching brands.

So then, how do businesses formulate and implement effective customer loyalty solutions? The solution lays in the application of big data analytics solutions to generate detailed insights into the customer journey. In short, analytics adds the differential in the creation of highly targeted content for the consumers, which in all probability leads to an increase in retention, conversions, or other results. In order to ensure the effectiveness of such marketing approaches, the businesses need data. This data would enable the segmentation of the audience, provide relevant calls-to-action and the delivery of services that empower the customer to view as important.

However, this brings back a pertinent question: Where do the brands or the marketers find consumer data is relevant as well as trustworthy, if their customers won’t provide it? The answer lies in the simple act of observing consumer activities along with their preferences that are in tandem with their external data sources. Further application of advanced big data analytics solutions can facilitate businesses to create a very accurate buyer profile, one that would allow their precise segmentation. The marketers stand a chance to redefine their loyalty scenario with the implementation of a more informed and facts-driven consumer engagement model. For 86% consumers (source: ipsos), personalization does have some impact on their purchase decisions.