Jan 19, 2017 4:02:12 AM | 10 Min Read

A View of Customer Loyalty in 2017 – Trends from an Exclusive Webinar with Snipp and Loyalty360

Posted By Snipp
A View of Customer Loyalty in 2017 – Trends from an Exclusive Webinar with Snipp and Loyalty360

Customer loyalty is evolving and, in 2017, there are some trends for brands to follow to elevate their customer engagement, customer experience, and brand loyalty.

During Tuesday’s Loyalty360 webinar titled, “The State of Loyalty in 2017 – An Exclusive Webinar with Snipp and Loyalty360,” presented by Snipp, four trends were discussed along with the essential elements of a successful loyalty program.

Christian Hausammann, global director of loyalty, Snipp; and Carlos Dunlap-Beard, vice president, loyalty solutions & business development at Snipp, were the featured webinar speakers.

Trend 1: Evolution of loyalty platforms
“Evolved technologies are creating enormous opportunities for brands to engage consumers with their loyalty platforms in unique ways, specially tailored to modern preferences,” Hausammann explained. “These technologies also solve specific challenges that some of the older mechanics face – such as receipt processing.”

Hausammann said there are certain advantages apps have, and there are certain advantages microsites have.

“Make sure any technology solution you undertake is strategic,” he said. “Don’t just adopt a technology for the sake of its novelty. Make sure it has an underlying business purpose that is aimed at meeting a specific objective. Every technology, including apps and microsites, have certain advantages and downsides. In the past, apps have been able to provide more data than microsites. This is quickly changing, and now both tools are great for accessing unique data about consumers that other solutions (such as pure loyalty card with POS integration systems) cannot access.”

Hausammann cited the Kellogg’s Family Rewards program, which was launched in 2012.

“Prior to launch, Kellogg certainly laid the foundation for how a great loyalty program should be,” he explained. “From the get-go, Kellogg was and is a points-based program. However, in the past, it has relied on codes on packs that consumers had to enter online to get their points, and, ultimately, exchange these points for a reward. This had a few challenges, such as being cumbersome for the user. But, there also there was no guarantee that if a consumer was entering a code it means they actually purchased the product. So there is no tie to purchase so that we can then later tie it to the product.”

What’s more, cost was a factor.

“Kellogg had 15-digit alphanumeric codes printed on the packaging, and the task of coordinating this with printing centers, with all the different types of products, was a very daunting one,” he said.

How did Snipp help out?

“The solution that Kellogg has implemented, which is a very elegant solution, consists of two parts,” Hausammann said. “The first part is the solution that enabled customers to simply take a photograph of the receipt. No app required. Simply snap a picture of receipt and send it in.”

Trend 2: Lifestyle loyalty programs

“Traditionally, we marketers were happy to gather demographic information,” Dunlap-Beard explained. “Later on we would get other lifestyle factors like hobbies and interests. But now, thanks to the evolution of technology, we can now gather all manners of information such as exercise/active behaviors, personal health information (with the member’s permission of course), social interactions, location tracking and even migration patterns. In fact, I recently worked with a retailer to incorporate the ability to alter communications and offers when the program member was residing at their summer, identify when he/she would begin migrating south for the winter and then shift the communications and promotional offers to fit their new Florida lifestyle. We now have the ability to better understand and provide more relevant, timely messages to customers.”

Dunlap-Beard pointed to some better technology options.

“The cool thing is lifestyle functionality doesn’t have to be a proprietary IT development for your organization,” he explained. “Most of these lifestyle tracking devices/services have a dedicated team in place whose primary responsibility is to seek out and enable value-add partner integrations.”

There are wearable devices: Fitbit, Garmin, and even an apple watch as examples. Devices that track activity, monitor heart rate and even provides prompts to stand up or interject a relaxation exercise periodically throughout the day.

Additional consideration needs to be given for smart home devices (e.g. Samsung SmartThings, Amazon’s Alexa, and Google Home, etc.)

“We already know that electronics and appliance manufacturers are making more and more smart products that can all be connected and managed via a single smart home device,” Dunlap-Beard said. “Now let’s connect those devices to our loyalty and engagement programs. Examples could be rewarding members for energy efficiency within their homes, as well as for their daily/weekly activities or exercises. It’s time to evolve and not continue the practice of making connecting to loyalty programs a separate or multi-step act. Today’s technology will allow us to get there. And isn’t that what we aspire to be–an essential and integrated part of our best customers’ lives? We’ve known that consumers don’t just sit at their computers to connect anymore. And now they’ve moved beyond just a smartphone. They are living their lives and the go, tracking their progress and literally their steps along the way. Therefore, we brands and loyalty service providers need to stay diligent about raising our game to stay connected while they’re on the go.”

Trend 3: Machine Learning
Hausammann listed four ways that businesses are using machine learning:
Making User-generated content valuable
Finding products faster
Engaging with customers in more meaningful ways
Understanding customer behavior to predict future actions

“If your company isn’t using machine learning to detect anomalies, recommend products, or predict churn, you will start doing it soon,” Hausammann said. “Because of the rapid generation of new data, availability of massive amounts of compute power, and ease of use of new ML platforms (whether it is from large technology companies like Amazon, Google, and Microsoft or from startups like Dato), we expect to see more and more applications that generate real-time predictions and continuously get better over time.”

Here is a basic process for implementing a Machine Learning discipline.
1. Gather appropriate data
When trying to predict the likelihood of an event occurring, we look at what has happened so far. We begin by gathering data about every customer visit to the site. This includes demographic information such as location and device type, as well as behavioral data such as how many pages they have viewed and how long they were on the site. 

2. Prepare and transform data
This step, while often overlooked, is usually the most work-intensive. Now that we have collected relevant data, we must change it into a form where it can be used with a machine learning algorithm. Categorical data, such as location or device type, usually needs to be binary-encoded. This is so that it can be recognized in a form that our algorithm can understand.
Numerical data often needs to be normalized. Many machine learning algorithms perform better when numbers are scaled between 0 and 1. For instance, the number of pages a customer has viewed would be normalized. We use these techniques on both the features and the labels, with the labels requiring binary-encoding. 

3. Choose a machine learning algorithm
When calculating the probability of an event occurring, there are various machine learning techniques to choose from. These techniques include decision trees, regression, Bayesian methods and deep learning (neural networks).

4. Train, test and re-evaluate the model
Having chosen a machine learning technique and prepared our training data, it’s time to train a model. We pass each set of features along with its corresponding label through the algorithm.

Trend Four: B2B Loyalty Programs

“We need to recognize that people are consumers at home and consumers while on the job,” Dunlap-Beard said. “However, although business buyers are still consuming, depending on the audience, their needs will differ. Therefore, to enable a best-in-class B2B loyalty strategy, the program and the platform needs to be flexible, allowing businesses to participate in a manner that best fits their structure and culture.”

For instance, Dunlap-Beard noted, many businesses and their administrators will want oversight, compliance, and benefits for the business (e.g. discount on services, certifications, continuing education, etc., – as well as regulatory control where applicable.

“This is especially true in healthcare and pharmaceuticals when you account for HIPPA regulations – or PCI compliance or Incentive-Based Compensation restrictions identified in the Dodd-Frank regulations,” he explained. “Staying out of the crosshairs of regulatory compliance officers is a must. From a flexibility standpoint, a B2B program should provide business customers with the option to choose institutional or individual contributor rewards and recognition. Some business program members may choose to pool all earnings from your loyalty program, and give the administrator the ability to redeem for rewards that can be given as recognition to top-performing sales reps or other employees as the organization sees fit.”
Dunlap-Beard said that the essential elements of a loyalty program comprise four foundational pillars:

  1. Gaining awareness by using existing methods of communicating with your customers, as well as seeking assistance from any partners. In addition to teasing, announcing and inviting members to enroll, we are also big believers in maintaining steady relevant messaging.
  2. Once we capture their attention, the enrollment process needs to be easy for members to join.
  3. Providing meaningful and clear ways to earn will be one of the most compelling reasons for your customers to join your program. Members should be allowed to earn for both purchase and non-purchase behaviors. The purchase part is a given. The non-purchase, but brand-friendly behaviors may include reading an article or blog from your site, referring a friend to join the program, writing a product review, etc. Those behaviors may not contribute immediately to the bottom line, however, they certainly have a value to your brand.
  4. And then there are the rewards. Customers – both consumer and business – like options…even if they never plan to redeem for that item. The redemption options should be a mix of low-, medium-, and high-valued items – at least as perceived by the program member. And if you have a brand that your customers are passionate about, it’s also a good idea to include brand and program branded redemption options.

“These are the essential elements of a winning loyalty program,” Dunlap-Beard said. “So by utilizing this process, while keeping in mind the four most influential trends for loyalty marketing this year and probably next year, you’re already off to a good start in 2017.” 

This article appeared in Loyalty360. January 18, 2016

Topics: SnippLoyalty, Loyalty, snipp news, Trends

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