It’s no longer enough for brands to just compete on factors like price, quality and value. They’re now battling it out in a more critical arena: customer experience. In order to come out on top, your brand will need to move beyond focusing on acquisitions and invest in customer loyalty long-term.
The good news is that you can expect a great return on your investment. Keeping an existing customer costs 5x less than acquiring a new one, and loyal customers deliver more revenue and a greater lifetime value or LTV (on average 10x as much as than their first purchase with your brand).
However, retention is not without its challenges, especially with the types of offer brands send to their customers. Many brands rely on mass, static offers, which treat all their customers the same. But these broad transactional offers do not build loyalty—research from Epsilon revealed that 80% of customers are more likely to purchase when brands offer personalized experiences. Customers now expect every contact they have with your brand to be highly relevant to them, which means you need to personalize every stage of the customer journey for each individual. This 1:1 relevancy is where a dynamic offer optimization can help.
Let’s take a step back and define customer journey — the complete sum of a consumer’s experiences with your brand, for their entire lifetime as a customer. However, it’s not what you should be focusing on. Because a customer’s journey isn’t linear. You need to focus on interactions that continue to engage and re-engage the customer, leading them to choose the brand again and again, which is called a “customer loyalty loop marketing model.”
The customer loyalty loop marketing is not necessarily linear. Yes it is true customers are entering a marketing funnel, but they could go around and come in and out before they purchase. And you want customers to go through your loyalty loop marketing and purchase over and over.
If you look at the loyalty loop marketing model, customers are actually entering at any moment, and it’s up to brands to create moments of inspiration, which could be a highly relevant loyalty offer. This leads to building trust and strengthening loyalty. Customers will then see and choose your brand every time they have a moment of inspiration to buy. By focusing on loyalty loop marketing, you’ll need to think beyond mass offers and orchestrate a truly engaging customer experience every time you communicate with customers.
That’s where relevant and individualized marketing offers come into play. By using data analytics for loyalty loop tools and activating those insights, brands can leverage dynamic offer optimization solutions to automate the construction of individualized offers and then use machine learning to continuously optimize those offers. Brands will then create true moments of inspiration that are relevant and highly valuable and customers will choose you over and over.
The customer loyalty loop only works well if each brand interaction is relevant to your customer and beneficial to your brand. Some of the challenges include existing marketing technology stacks, which are not designed for these types of loyalty loop marketing.
Currently, most marketers are personalizing content only. They can change first names, images and other content for their customers. However, this is not true individualization, and it doesn’t go far enough. Today’s consumers have high expectations because of social media newsfeeds, Google ads and even Netflix. They want offers to be completely tailored to them, where points, products and even rewards are individualized and thus relevant to them.
When we look at the loyalty loop model, its prime feature is the loyalty loop trigger. This is the stimulus for a customer to purchase a product or service. It’s the process of creating the need to buy through marketing, and loyalty loop marketing motivates the customer to skip evaluation and consideration and jump from loyalty loop trigger to purchase. It shortens the buying cycle while increasing true brand loyalty. Here’s the breakdown:
Trigger - The stimulus to buy a product and the process of creating a need in the customer’s mind through marketing communications or offers.
Initial Consideration Set - This is when a customer researches a product via online or offline.
Active Evaluation - When customers compare different products in terms of features, price, reviews, return policy, etc.
Moment of Purchase - The customer buys a product or service.
Post-Purchase - After a customer buys, they may share their experience via review or WOM.
To design a customer journey that focuses on data analytics for loyalty loop tools and loyalty loop triggers, you’ll need to deliver individually personalized experiences your customers want while creating the repeat purchase opportunities you need to sustain growth.
Choose offer optimization platforms that gather customer data from all of your disparate sources, such as loyalty programs and data platforms that use machine learning (ML) to gain actionable insights into each customer’s motivations, interests and habits. For example, offer optimization platforms use ML to develop dynamic loyalty offers for each individual customer, and distributes them automatically across all of your marketing channels.
That’s just the beginning, though, because the ML algorithms never stop learning. They continue to study each customer interaction, and fine-tune each customer’s offers and experience accordingly. This intelligent automation allows you to scale to millions of individualized offers that get ever more effective—what we call true 1:1 relevancy.
Building the world’s most personalized brand
One example is Formation, which enables Starbucks’ individualized offers. The company has always invested in retention by providing robust rewards, but they wanted to take their customer experience to the next level. Their ambitious goal was to become the world’s most personalized brand, and use individualized offers to grow revenue among their 18.9 million program members.
Starbucks used Formation’s powerful offer optimization platform to synthesize their disparate data sources – including transaction, product, loyalty and store data. Using this data, our machine learning algorithms personalized and optimized the offer selection for each rewards member.
Offers were individualized in numerous ways, including the number and type of actions required, the offer categories and products, and the amount and type of rewards. Formation also made it easy for the global coffee chain to deploy offers across channels by automating offer assembly, offer management, reward fulfillment and KPI measurement and tracking.
Using Formation, Starbucks was able to increase their number of offer variations 100x, while reducing the time required to develop and launch offers 10x, ultimately resulting in a 20% increase in spending by U.S. loyalty program members.
Individualization meets gamification
Brands like Starbucks are able to achieve such dramatic lift thanks to Formation’s unique mix of 1:1 individualization and gamification. Of course, gamification itself is nothing new—marketers have been applying elements of game play for decades to boost customer motivation. In loyalty offers, it’s been prevalent since United Airlines introduced the first modern frequent-flyer program in 1972. And who can forget the now-infamous McDonald’s Monopoly game of the 90’s and 00’s.
Today’s use of gamification applies game mechanics like tiered status, leveling up, unlocks, missions, goal setting and progress markers to foster engagement and ongoing loyalty. Even gaming skeptics will see the subtle use of gamification in their daily lives: LinkedIn’s progress bar prompts you to complete your profile, while Reddit’s upvote system and Karma scores motivate users to keep engaging with the platform.
Gamification can be highly engaging for customers because it taps into goal-oriented motivation, but the way it’s typically practiced has a couple of drawbacks. The first is that creating and launching a gamified experience is usually very resource intensive. Secondly, it’s usually a one-size-fits-all experience, which means your brand and your customer are both missing out on the benefits of personalization.
Formation is unique because it’s the only marketing solution that automates the entire process of these two highly effective motivators, 1:1 individualization and gamification, to access the untapped growth potential in your existing customer base. Our technology enables us to meet your customers wherever they are on their journey, and deliver them individually relevant offers that also nudge their purchasing behavior to meet your goals. Offers can be developed to increase buying frequency, reward and reinforce behavior, introduce new products (cross-sell), upsell to high value products or even onboard new customers and re-engage inactive ones.
Formation’s offer library has proprietary customer journey templates that help brands combine 1:1 individualization with proven gamification or incremental behavior change templates. Then with the automation, you’ll optimize and scale the entire process with smarter and faster experimentation. As our solution leverages machine learning algorithms to analyze your customer data, these templates are pre-wired to ingest data insights to configure the templates quickly and automatically, getting out to market in just days instead of months of manual work.
We’ll use the Starbucks example to illustrate how offers can guide the customer journey to reinforce the loyalty loop.
Let’s say our customer is a fan of black coffee. The ML system will analyze his motivations and interactions with the brand to date, and deliver the following series of offers:
Increase frequency: The customer is given a repeat action offer that we call a product dash, e.g. buy a black coffee 5 times to earn 500 points.
The product, number of visits and incentive are all personalized to the customer, helping to motivate them to visit more often.
Over time, the product dash reinforces the behavior more effectively than a one-size-fits-all offer like a punch card.
Introduce new product (cross-sell): Once the customer is visiting more frequently, their offer may shift to introducing a higher margin item such as a breakfast sandwich.
The new product may be introduced as part of a quest, a series of different actions that earn an incentive at the end.
Quest actions for this customer might include purchasing two black coffees one week followed by a black coffee + sandwich the next week.
In the above scenario, 1:1 relevancy delivers a clear message that recognizes the customer’s habits and preferences, while gamification incentivizes the steps they need to take and tracks their progress to create natural recursion. This combination of motivators works for any industry that can utilize a loyalty program, from grocery and retail to hospitality and financial services.
You may already realize that the majority of your business comes from existing customers. Yet these customers will remain a largely untapped revenue source if you don’t deliver the right experience to motivate them.
By analyzing large amounts of your customer data, our ML solution identifies every customer’s unique preferences, motivations and desires. It uses that information to generate gamified offers that are personalized to each individual. This keeps your brand hyper-relevant to them throughout their journey, maximizing engagement, conversion and revenue.
Offer optimization platforms deliver these results much faster than traditional methods, enabling your team to scale to millions of personalized offers in weeks, not months. Over time, the ML engine continues learning from each customer interaction, so offers keep getting smarter and more effective.
Customers using Formation to engage their most loyal customers are already seeing up to a 3x increase in net incremental revenue, 2x increase in marketing efficiency and 10x faster marketing execution. Find out how much growth your brand can realize. Contact us to schedule a demo.