The 5 biggest loyalty data challenges and how to solve them

"Companies that gain insight from their data are three times more likely to outperform their competitors," Forrester Analytics predicts.

Talking about the importance of loyalty program data is easy enough, but how can you get the insights you need to deliver more accurate personalisation? And what are the challenges companies face when handling data?

Think about how many times you’ve had to fill out a survey when browsing a website - or how many times you might’ve been annoyed by long and hard-to-understand Terms of Services or cookie consent.

Data has to be easy to get for companies and at the same time easy to share for customers, otherwise, it’ll all be useless - and this is just one of the biggest loyalty data challenges brands need to be aware of.

What is loyalty program data?

Loyalty program data refers to the valuable information collected through customer loyalty initiatives. This data represents first-party insights into customer behaviour, including their purchasing frequency, demographics, and interests.

By analysing loyalty data, businesses gain a deeper understanding of their customers, enabling them to tailor their offerings and enhance customer experiences.

Loyalty program data serves as a powerful tool for driving customer engagement, personalisation, and targeted marketing strategies.

Your loyalty program needs data in order to create value and resonate with your customers. The use of first-party customer data in your loyalty program allows you to provide personalised offers to customers and maximize your return on investment.

In fact, 92% of marketers believe using data to understand what your customers want is critical to growth. 90% of marketers agree that this approach significantly contributes to profitability.

So, loyalty program data-driven marketing is something that could be of interest, but what are the main challenges brands usually face when it comes to data?

1. Disconnected Data Sources

There are endless areas in which you can collect loyalty data, and you might not even know it: transactional data, behaviour data, demographic data, activity data, and many more, collected across brands, business units, and regions.

The datasets are likely to be in different formats, different languages, and to come from different sources. They may also be stored in a different system.

Creating useful insights from this data is time-consuming, expensive, and manual, but the end result is an efficiently created single customer view that all business functions can use to drive their individual priorities.

Unifying the massive amounts of customer data that companies collect across all channels and touchpoints is one of the critical issues with customer loyalty program data.

Only 38% of marketers say they have the customer segment and persona data they need in the right format to make good marketing decisions, the Capgemini Research Institute CMO survey in March and April 2021 found.

Our Loyalty Console dashboard makes all this information easily accessible, allowing complete visibility over what customers are doing and when, and providing all the information to effectively market to them.

2. Data Not Consolidated

Once you solve the first challenge, connecting all disconnected data sources, you’re likely still facing a second issue: is this customer view clean? Are all duplicate profiles removed? Are unknown and known identities unified into a full profile?

Data cleanliness, consolidation, and unification are all challenges that you need to solve to positively impact how efficiently all functions of an organisation interact with customers.

All parts of your team might be affected by this: marketers might be including duplicate profiles in their campaigns, logistics might have an incorrect view of the total number of customers, etc.

Loyalty data is only useful if it’s easily accessible and understandable. Our system allows you to create charts by combining data from across the system, letting you utilise your very own dashboard of custom graphs to make everything intelligible and easily actionable.

3. Obscure Data Permission

Another challenge is understanding how to improve the way customers are asked to grant data permissions and the experience they have adjusting those permissions.

What would you say as a customer if you walked into a store and security asked for identity documents before you could shop, forcing them to sign a complicated agreement?

Too often privacy and data use terms are intentionally obscured by things like long and hard-to-understand Terms of Service text that customers have to check off on, or cookie consent where customers have a hard time finding the opt-out choices.

These poor customer experiences build bad communication and trust. Brands need to review their end-to-end loyalty data collection experience to see where it can be improved.

4. Customer Segmentation

According to Salesforce, 97% of marketers witnessed a rise in business outcomes as a result of personalisation.

The perfect customer experience requires organizations to deliver personalized content on the channel and at the time customers prefer.

Organisations are spending money marketing to audiences who may never buy for a variety of reasons rather than focusing on the marketing investment where it will have the biggest impact.

The most common challenge to achieving real optimisation is when you let a generic message be broadcast to generalised segments and audiences.

A 360-degree view of each customer will enable you to learn more about their demographics, transactional behaviour, engagement statistics, and personal preferences.

A loyalty program is the ideal starting point for this. You can also use AI to do most of the legwork. AI modelling can be used in loyalty programs to help you find insights within your customer database.

5. Not Preparing for Customer Data Information Requests

As a result of regular news stories about corporate data breaches and how social media uses data, public awareness is increasing around how personal and loyalty data is collected, stored, protected, and used.

When it comes to data collection, companies need to prepare for questions from customers.

Across the globe, privacy laws aim to empower individuals to be in control over their data, empowering them to understand how, by whom, and why their personal data is being used.

Businesses that collect personal data are obligated to respond to those questions and manage personal data in a compliant way. Gartner’s predictions for the future of privacy claim that privacy is today what “organic” or “cruelty-free” was in the past decade.

Responding to those requests may be a challenge for brands, so the time to plan is now.