How analytics can drive loyalty programme effectiveness
In 2016, Nielsen found that 89% of British consumers were members of a loyalty scheme, yet just 51% would choose to shop with a retailer because they were part of its loyalty programme.
Loyalty programmes are commonplace these days, but to create one that’s truly effective, retailers have to tailor the experience to fit individual shoppers.
As Comarch’s Future of Retail report found, 87% of UK consumers surveyed said that the quality of loyalty rewards on offer were important triggers to them using the scheme.
Brands that run loyalty programmes need to realise that loyalty works both ways, and if shoppers feel that their needs aren’t being met, why should they remain loyal?
How data can help create effective loyalty programmes
There’s an abundance of data that retailers can use to help craft a tailored loyalty programme. From purchase history to journey-to-purchase, and even social media engagement, the sources of customer data are growing by the day.
The right software, applied correctly, can analyse this data and potentially drive higher profits and higher levels of customer satisfaction for the brand. This data analysis is a necessary part of a long-term, effective loyalty programme.
As SAS research noted “There is a strong correlation between loyalty programme effectiveness and the use of data and analytics to develop and measure loyalty programme strategy.”
Building valuable customer relationships as part of a successful loyalty programme
All brands want valuable customer relationships. However, fragmented data makes it almost impossible to understand customers as individuals.
Who are your customers? Which are the most profitable? How do your promotions impact sales? Is your retention programme reducing churn? These can be difficult questions to answer for any brand.
But when data analytics are applied correctly, they provide insight not only into customer behaviour, but their value and the effectiveness of the brand’s campaign. They can also identify potential savings and ways to increase revenue.
Increasing customer retention using unique loyalty rewards
The fundamental goal of any loyalty programme is to increase customer retention, and maximise the value of each customer. To achieve that goal you have to analyse customer buying patterns, their preferences, needs and opinions, no matter how or where they give them – be it in-store, on social media or online
This data is then analysed to get an accurate picture of the kind of rewards that individual customers crave. It gives the brand a chance to surprise and delight, and to offer a comprehensive reward catalogue that makes shoppers want to earn points for.
It’s not just physical rewards either. The data may show that some customers have no issue with the current rewards on offer – what they want it a personal touch; something to show that the brand knows who they are and understands what’s important to them.
Some brands send offers to customers on their birthdays, for example. While this is a nice sentiment, how much more effective would it be if the offer was something that they really wanted rather than a generic, “we’ve noticed that you buy cat food, here’s 50p off Whiskas”?
Real-time, cross-channel couponing (based on data analytics insight) is also important. Customers want offers that they can take advantage of at the POS, or on their mobiles.
The next challenge for brands will lie in using recommendation engines to work out what offer should be served to which customer, and what time and channel would be most effective for delivery.
The impact of social data on loyalty analysis
According to figures from the Office of National Statistics, 66% of UK adults are social network users (that’s a 3% increase from 2016).
Whether the brand acknowledges their posts or not, customers are using social media to critique, praise and share content about the brands they shop with. These posts can provide significant insight into what people really think about the brands they shop with - if the correct analytics tools are used.
However, with the new GDPR and data protection laws coming into force soon, brands will need to get a customer’s permission before using their personal data for this analysis.
Once permission is given, this data can be used to inform business decisions, by:
- Finding out what customers really think. By monitoring keywords, businesses can see both what’s being said about them, and understand the emotion behind the language. Businesses are able solve issues before they become a bigger problem, and expand on areas that customers love – both of which will increase customer satisfaction and make them more inclined to stay loyal.
- Offering precision targeting of promotions. Social listening enables brands to target its promotions and offers much more precisely than they would be able to using traditional marketing.
- Offering proof of results. By monitoring social content, brands can see the results of their loyalty promotions offered digitally and offline. This instant feedback can be used to improve future promotions and develop compelling content.
- Helping to identify brand ambassadors. By analysing the brands social mentions, it can see who is talking enthusiastically about the brand and its loyalty initiatives. Brands can then work out a way to recognise and reward these people (even something as simple as a “thank you” can go a long way).
- Incorporating insights into the loyalty programme. Brands can make full use of this social data by incorporating it into their loyalty programme databases along with other cross-channel data. This way the brand will be able to see a comprehensive picture of customer opinion and behaviour.
Let’s try to imagine what the future for loyalty analytics holds. We can assume that at some point real-time analytics insight will be available at every customer touch-point. This means that every loyalty programme can be tailored to each individual member and what they want from their relationship with the brand, no matter which industry the business is in.