5 Platforms For Making Tailored Recommendations Across Digital Channels

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Walk into the average big box retail store, and you’ll find a dizzying array of products in different styles, colors, and sizes. The scene can be overwhelming, and based on what research tells us, it’s not what shoppers want.

As 2016 winds down and consumers finish up their last minute holiday shopping, they’re wanting to spend more time at retailers with limited, relevant, and highly-targeted product collections. This is especially true for consumers shopping online. According to a survey by Magnetic and Retail TouchPoints, 81% of online shoppers want to “find what they’re looking for, see product reviews and recommendations, and ultimately buy the product when and how they want.”

Getting the right product in front of the right consumer at the right time is the holy grail for both online and offline retailers, and it’s being made easier by new tailored recommendation platforms that use natural language interactions to assist shoppers across multiple digital channels. Here are five examples of technology solutions that retailers and brands are using to make more tailored recommendations to shoppers across both online and offline channels.

1. Expert Personal Shopper (XPS): Replacing keyword searches with guided conversations
Acquired by IBM in November, Expert Personal Shopper (or XPS) from Fluid is a “dialogue-based product recommendation platform” that personalizes the customer experience. In order to do this, XPS digests millions of data points and content around specific categories or products. It then creates “experiences” where shoppers can engage in online conversations in the same way they’d talk to in-store associates. For example, XPS might ask an online shopper “What are you looking for in a new lipstick?” If the shopper responds with, “I want something that will stay on all day,” then the platform would scan the retailer’s product catalog and provide the customer with a list of relevant products. XPS is powered by IBM’s Watson cognitive computing technology, and it’s already been put into use by major retailers like The North Face.

2. Certona: Omnichannel personalization for brands and retailers
Certona’s “1:1 real-time personalization technology” utilizes real-time context, customer profiling, and dynamic merchandising. When combined, these elements enable marketers to personalize not just their websites, but also their mobile apps, contact centers, and even in-store. Marketers can automatically personalize the offers, images, videos, advice, and driving directions that shoppers see. For example, based on the behavioral data Certona has collected about a shopper, the software may re-order the search results to highlight those products the customer is most likely to be interested in. Certona is used by retailers and brands like Forever 21, Hot Topic, and Lenox.

3. Personyze: Personalized recommendations based on visitor characteristics
Personyze has developed a SaaS platform for marketers that want real-time visitor segmentation and site personalization. The company tracks more than 70 behavioral characteristics, including social media usage, onsite behavior, and even geo-location, and then uses the information for on-site product targeting. For example, if a retailer sells sporting apparel and a visitor’s interest patterns indicate he is an avid Lakers fan, then the system will load products with that team’s logo on the store’s homepage the next time he visits. Personyze can also customize website content based on a visitor’s real-time weather, so a car dealership might promote convertibles to people who visit its website on a sunny day and SUVs to people who visit when it’s snowing outside.

4. 4-Tell: Creating online experiences similar to brick-and-mortar
4-Tell combines the “wisdom of the crowds” with advanced data analytics and a retailer’s own product knowledge to better engage digital customers. The e-commerce software firm generates personalized product recommendations to increase conversions. It automatically recommends products that shoppers are most likely to buy based on their browsing behaviors and purchasing histories, and it phases those recommendations into shopping carts, product pages, and website search results. The company’s “Boost Recommendations Engine” allows for cross-channel personalization across web, email, mobile and in-store.
Merchants that have used 4-Tell’s Boost products include Columbia Sportswear and BodyCandy.

5. SearchSpring: Intelligent product recommendations
SearchSpring has its own take on personalization, with a merchandising module that uses machine learning and predictive artificial intelligence to helps shoppers find the right products in less time. The e-commerce site search and navigation platform captures user search behavior and combines it with product data and business logic. It can then deliver shoppers with relevant products depending on where they’re at on the path to purchase, regardless of what device they’re using. SearchSpring even uses custom redirects to automatically route visitors to relevant product pages depending on the search terms they enter. SearchSpring is used by Remington and Drybar.

Know of other platforms for making tailored recommendations across digital channels? Leave a description in the comments.

Stephanie Miles is a senior editor at Street Fight.



Stephanie Miles is a journalist who covers personal finance, technology, and real estate. As Street Fight’s senior editor, she is particularly interested in how local merchants and national brands are utilizing hyperlocal technology to reach consumers. She has written for FHM, the Daily News, Working World, Gawker, Cityfile, and Recessionwire.