For many retailers, one activity that promises a valuable insight into their customers is running a loyalty scheme. This can generate huge amounts of information about what their consumers are actually doing, so it is often seen as a good way to guarantee results from analytics operations.
But the reality is often very different, as many firms find themselves without any idea of how best to use this information. In fact, a recent study by the International Institute for Analytics (IIA) revealed just 16 per cent of companies rate their loyalty programmes are highly effective, Enterprise Apps Today reports.
This is therefore a clear illustration of the fact that gathering data is only the start of the challenge when it comes to running a good analytics initiative. To make the most of this, it is also vital that companies are looking at the right data, asking the most appropriate questions, and ensuring they can get actionable insights from their processes.
One issue suggested by chief executive of the IIA Jack Phillips is that many brands may be struggling to cope with the fast-moving nature of analytics. "The landscape of new innovative techniques is moving so quickly, it's hard to come up with something unique and sustainable," he said, adding: "An inability to get to fine-grained data makes it difficult to tailor services to consumers."
Among the key challenges facing businesses when it comes to making their loyalty programmes work well include offering rewards that customers will truly value and measuring the effectiveness of their efforts. Both of these were cited as key issues by 45 per cent of respondents.
Other issues include how firms differentiate their offering from those of their competitors, named by 43 per cent of respondents. Research by Maritz has noted the average consumer is a member of 7.4 loyalty schemes, but is only active in 4.7 of these – so coping with this overload and finding ways to stand out from the crowd will be essential.
Another potential solution to improve loyalty programmes is to be more innovative in how companies interpret the data they use, going beyond the obvious. The study found the majority of actions taken as a result of their analytics processes are based around transactional data such as how many points they've earned and what they are buying. So for instance, this can be used to offer people discounts on products they're known to purchase frequently.
The problem with this is it does not really tell businesses anything new about their customer, as the results they get will always be the same.
Mr Phillips said tackling this involved being creative and considering what other sources of data they can use to provide insight into their customers.
For instance, among organisations that described their loyalty programmes as ineffective, just 14 per cent use information gleaned from social media to inform their decision-making. This rose to 25 per cent among firms that said they had effective strategies, and 37 per cent in organisations that rated their initiatives as highly effective.
As another example, Mr Phillips added: "If I pass the dry cleaner every day on my way to get a drink at Starbucks, at some point maybe the dry cleaner will say, 'I see this guy goes to get coffee every morning. Can we make it easier for him to drop off his dry cleaning?'
"Loyalty program leaders are asking 'what is the data I can control?' and then reverse-engineering unique features that could be based on that data."