Machine learning helps personalize the gift card experience across retail channels

Epipoli uses SAS^® artificial intelligence and customer intelligence solutions to craft relevant, real-time offers for customers

Omnichannel marketing is the holy grail for today’s retailers who are looking to offer a consistent customer experience, personalized promotions and interactions throughout the customer journey across multiple purchase channels, including brick-and-mortar stores, e-commerce websites, mobile apps and social media.

Epipoli brings one more channel to the omnichannel table – gift cards. As one of the leading gift card companies in Europe, Epipoli was the first company to create a platform to automatically manage all processes related to the issuance and use of gift cards and deals that span both physical gift cards and digital cards.

Now Epipoli is taking its offerings to the next level by expanding its operations to digital channels with its new brand, Groupalia.it, one of the leading digital deals players, and by using SAS analytics and artificial intelligence (AI) solutions to combine the data it collects from its online customer touchpoints with transactional data from individual customers to power one-to-one marketing, customer loyalty and performance incentive programs.

Better understanding customers

With roughly 250 partners and more than 50,000 points of sale, Epipoli uses advanced technologies to create customer relationship marketing solutions. In the process, it has collected terabytes of data from retailer transactions and digital channels. Today, Epipoli has a merchant and consumer database that federates data from nearly 10 million people. It aims to use this data to better understand customers so it can personalize each interaction in real time.

“Marketers often have a distorted and conformist image of customers because we only see the final effects of a behavior and neglect to consider the causes,” says Gaetano Giannetto, Chief Executive Officer of Epipoli. “We need to rely not on variables like income, but rather on passions, preferences and the network of relationships every person has.”

The challenge for Epipoli is to make sense of all the data it collects in a way that allows the company to personalize contacts with customers. “Controlling every point of contact requires an ‘always on’ analysis engine,” Giannetto says. “We must have a series of indicators and machines always ready to respond dynamically, whether the customers are in the street, in front of a physical store or on their favorite social network. With machine learning models from SAS, we can enhance data, identify user profiles automatically and understand which of the various channels can become the optimal contact point.”

Structuring and consolidating big data

The first step Epipoli has taken toward realizing this vision has been to develop a big data analytics platform that properly structures its data. Epipoli has integrated SAS Customer Intelligence 360 with its e-commerce, loyalty and CRM systems as well as the systems at Groupalia.it. It uses SAS Customer Intelligence 360 to collect data about traffic, users and behavior useful for profiling customers on different touchpoints (catalogs, site prepaid cards and loyalty sites) and enrich it with transactional data from individual customer profiles.

“Our SAS solution is about collecting, processing and analyzing data in real time to improve customer understanding so we can strengthen the customer experience,” Giannetto says.

With SAS in place, Epipoli has:

• Reduced the cost of customer acquisition by 34 percent.
• Optimized marketing spending by 26 percent.
• Increased its customer base by 11 percent.
• Increased the average value of transactions by 29 percent.
• Increased conversion rates by 23 percent.
• Increased profit margins by 0.8 percent.
• Grown customer lifetime value.

Moving toward ever greater personalization

Epipoli is in the early stages of using SAS Visual Analytics and SAS Visual Statistics to analyze customer data coming from cards and e-commerce worlds. It will use the insights provided by the models to identify new market segments, make purchase recommendations and generate next best offers.

Looking ahead, Epipoli will integrate SAS Real-Time Decision Manager and machine learning with a dynamic discovery interface that looks at transactional and behavioral data in real time to provide personalized offers, or series of offers, when it issues a prepaid card to retailers. For example, when a consumer purchases a card from a retailer and its PIN is issued, the card could deliver a series of localized deals – in any or many channels – personalized according to the location, customer profile and profitability.

Epipoli also plans to provide a similar service to help employers manage employee benefits. For instance, employers might offer a personalized and compelling range of prepaid cards and digital deals to employees through a self-service portal.

And finally, the company hopes to use the platform in its role as a marketing and data partner to help other companies find ways to monetize their data while complying with the General Data Protection Regulation (GDPR).

“My highest aspiration has always been to create value in the most transparent way possible,” Giannetto says. “This is undoubtedly the key to beating the competition.”