It is well acknowledged that acquiring customers is more difficult than retaining them, and it is usually more lucrative and beneficial to maintain relationships, in terms of cost savings, a greater ROI on marketing budgets and creating less impact on resources.
Now with the evolution of big data, businesses have more opportunities to identify and reward their most loyal customers. However, in the competitive landscape of customer loyalty schemes it is important to establish what loyalty truly looks like, before developing and implementing a loyalty strategy using data science and analytics.
What is a Loyal Customer?
Loyalty implies an allegiance, some may suggest monogamously, to a brand. It is the overriding ideology that customers will continue to shop with a company or retailer repeatedly, in spite of contributing factors made by the competition. Take, for example, mobile users and the battle of Apple versus Android. Despite changes in product features, pricing, promotions etc. customers stay loyal to their preferred brand, with the leading brand safe in the knowledge it would take huge investment by the competitor to change this brand perception and loyalty.
For lower ticket items, where the perceived brand value may have less of an impact on customer purchasing power, loyalty schemes are in place to encourage shoppers to continue returning to their outlets, based on targeted loyalty rewards. Over recent decades, sophisticated loyalty schemes have exploded from supermarkets across airlines to financial services, with brands offering customers rewards in exchange for their data.
Yet an ideology might be all that it is - in the retail world, customer loyalty is therefore about achieving a little extra goodwill, a slight margin of preference and incremental shift in buying behaviour to maximise financial success and performance. Businesses acknowledge that customers will not shop with one for all their needs, however the opportunity for rewards and additional benefits can be enough to incite a change in customer behaviour and encourage their loyalty - at least until the next sales opportunity.
Loyalty Scheme Opportunities
Due to the requirement for consent and the ‘sign-up’ nature of loyalty programmes, they enable businesses to quickly and systematically collect customer data and engage directly with customers in line with GDPR requirements. In exchange, customers receive additional benefits, from offering rewards and additional privileges or services. The opportunities, therefore, for businesses adopting a loyalty programme are far-reaching both financially and non-financially.
Mass customisation of marketing communications.
Understand customers; their behaviour, preferences, habits etc. and track trends easily.
More purchases more often directly affects the bottom line.
Reward loyalty by giving discounts to best customers and adjusting the real price for certain customers.
Promotes trust and club feel to make customers feel part of the brand.
Minimise waste particularly with store/range planning and operations.
Asset value of the customer data.
Develop partnership relationships and use data to negotiate with partners.
Fundamentally, in order for a loyalty scheme to prosper, the business must be aligned and therefore is dependent on the following factors:
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Strategic: Loyalty must be at the heart of the business, reflecting the brand’s core strengths and used as a tool alongside the business/operational/retail fundamentals e.g. proposition, brand values, range offering, pricing, promotions, channel strategy etc.
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Long Term: Though loyalty schemes may be supported by tactical quick wins, there must be a long term view of growing customer value. Focusing on board, short term goals will impede the loyalty strategy.
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Commitment: All business stakeholders and employees should love the proposition and understand the importance to customers and business in the future. If it is not internally represented, businesses will not be able to insight change in behaviour.
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Return: Loyalty programmes must balance the cost of implementation and managing the scheme with the overall customer uplift to ensure return on investment.
Loyalty programmes done right, not only increase the number of loyal customers by reinforcing the decision to shop, they deliver return on investment and build and reinforce brand equity by rewarding committed behaviours. Customer loyalty, therefore, is not just a successful marketing exercise or card sign up scheme, it is part of the companies’ ethos to get everything right and aligned for the customer while building an effective pool of big data.
Loyalty Scheme Challenges
Despite the obvious benefits for businesses to run loyalty programmes, there are still a number of both internal and external challenges that a company faces in implementing these strategies.
Customers can feel a sense of Big Brother culture.
Loyalty programmes are a zero sum game & they are a bribe.
Loyalty schemes can peak when customers do, but be irrelevant afterwards e.g. redecorating, major purchase.
Identifying the incremental sales to pay for it. Additional customer profits outweigh loyalty programme investment and loyalty promotion costs.
Customers just want lower prices.
Loyalty schemes can feel like a “con”… I spend all year but still miss out… I must be paying for other people...
“Top Tier” Loyalty schemes can seem exclusive and alienate lower value customers.
Loyalty schemes can create a “club”, but I’m not good enough to be a member...
On top of this, increased regulation around collecting customer data, with GDPR regulation, cookie policies and the like, customers are becoming more savvy to giving away their data in an attempt to avoid mass irrelevant marketing. Companies have to be far more transparent in why they are collecting this data, and the value it will give to the client in exchange. With so many challenges to contend with, we see the following common failures that lead to unsuccessful loyalty schemes:
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Poor programme communication: Communications not used to grow spend, making scheme unprofitable.
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Low redemption rates: Customers do not redeem rewards, therefore see no benefit and stop taking part.
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Not enough customers: Few schemes attract a critical mass of customers to justify operation costs.
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High set up costs: Costs incurred are too high to recover from incremental customer spend.
Customer loyalty is therefore highly driven and dependent on a strategy that incorporates all aspects of the business and adds value by effectively implementing data led insights.
Using Customer Data to Find Your Most Loyal Customers
A common challenge for businesses is not only identifying how they should be using data to establish who their most loyal customers are, but what action to take when the loyal customers are clearly visible. There is more to winning customer loyalty and repeat business than offering a loyalty card (AC Nielson Study, 2004) and thus the loyalty scheme should look to reinforce the decision to shop and increase the margin of preference.
A data-driven approach to loyalty engages and aligns all aspects of the business, operationalising the loyalty strategy to extend beyond marketing communications to deliver customer value. Thus customer engagement and communications can be seen as a baseline of effective data implementation, which can be expanded in pricing and promotions; focusing on ranges and services; driving operational efficiencies and; localising stores and integrated channels, to deliver a major uplift in sales/margins.
Implemented correctly, data offers powerful insights to aid decision making around customer loyalty:
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Spot trends and react more quickly to competitors;
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Reduce waste from poor targeting of limited resources;
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Get prices, product range and promotions right for customers;
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Develop new products that customers want;
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Make communications relevant;
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Promote trust;
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Measure success.
Our Data-Driven Approach to Customer Loyalty
By putting data to work, we help businesses to identify their loyal customers and deliver a successful loyalty scheme. Successful loyalty programmes embed big data in their strategy and use it across all parts of the customer journey and experience to incite meaningful change and strategic action.
Data Layer
For a loyalty programme to work effectively the data must be warehoused and managed effectively so that useful analysis can occur.
Our data engineers and data operations experts support data management across all aspects of the customer journey to drive insight on customer buying behaviour, response rates to marketing communications and all aspects of the customer relationship management, all aligned with best practise and governance.
A sound data architecture and management process can also support 3rd party data sources (e.g. OpenSource) to help build and evolve the customer data asset through strong data partnerships.
Analytics Layer
From a strong data layer, businesses can begin to drive sound insights using a variety of data science and analytic technologies. An example of this is building segmentations to begin creating a profile of customers that react to certain messages or promotions.
With these insights businesses can shape other analytical solutions and machine learning techniques to model and predict behaviours, with the aim of making more strategic decisions, including adapting their offering in store, store promotions, etc.
Decision Layer
With clear customer insight obtained in the data and analysis layers, businesses can build out the long term, strategic decisions of their loyalty scheme.
We have supported businesses in developing a target communication and response plan that tracks performance and enables tactical communications to shape customer behaviour, to get the most out of their loyalty schemes and improve redemption rates.
Sector Specific Loyalty
While we have acknowledged loyalty (predominantly) in the retail sector for grocery stores, ‘customer loyalty’ takes different guises across different sectors, based on customers’ purchase behaviour. For this reason the measures of successful loyalty implementation will look different across every sector and will require a different set of objectives and tailored measurement approach specific to the business. Examples of this can be seen below:
Data provides a powerful tool from which powerful customer insights can be driven to underpin a loyalty scheme. If you are looking to understand and develop your customer loyalty strategy, specific to your business objectives, get in touch with our team of loyalty specialists.
Alternatively, take a look at our featured insights for more of our strategic expertise or for practical insight look at our case studies to see how our teams have been helping companies in putting data to work and unlocking the potential of loyalty.