…and it is your customer data.
Nine out of ten purchases still take place in the store. That means that with each swipe of the credit card, customers send a strong signal of preference by means purchase. But today this signal is lost into one of these: DMP, CRM, or another three-letter acronym for your data sinks.
So why not take make use of this rich data?
Point-Of-Sale (POS) data can provide insights into the real-time shopping trends in a local area or what items/brands an individual shopper prefers and/or has already purchased. It’s only logical that with a bit of wizardry with this data, you should be able build better models that represent your shopper base and provide more relevant personalization for shoppers regardless of the channel they are utilizing. POS data is proving already to help supercharge online personalization for web, mobile and email as some of our more innovative retailing partners are finding.
We have worked with a few adventurous retailers ($10B+ office supplies retailer and $1B+ upscale department store), to quickly test this hypothesis on these next generation recommendation models. We integrated in-store transactions into the Relevance Cloud™ and ran a test. One that used offline+online purchase data to build recommendation models and a control version that used just the online purchase data.
After 45 days, we found that strategies that used offline+online data drove +1% incremental lift in revenue per session sitewide (beyond the performance of existing recommendations). One percent lift may not seem much at first glance, but this is a significant return for billion-dollar retailers with little effort. And there is even more room for improvement. The retailers included in this test did not have a perfect offline-to-online product catalog overlap, meaning there is still incremental value that can be derived once these SKUs are resolved.
In the process we also discovered some key insights about the omnichannel shopper’s behavior:
Never leave another customer data set at the till again
Offline data ingestion is a simple process. RichRelevance Omnichannel strategies take the following datatypes and offer personalization based on a 360-degree view of individual consumers:
POS Transactions: Purchases, orders and returns that contains a purchase date, item(s), customer ID, and monetary value.
Shopper Segments and Attributes: Customer or household segments such as gender, location, loyalty tier, etc. from homegrown databases, CRM records or third-party resources (Merkle, Acxiom, LiveRamp, BlueKai, etc.).
So when emptying your cash register at the end of the day…
…don’t leave your customer data behind. Put it to work to get more out of your online personalization and build richer experiences.
Learn more about Offline Data Ingestion.
They say you can’t put a price on love, but Netflix CPO, Neil Hunt, recently put a price on the value of better recommendations for his customers, and that figure is half a billion dollars.
In his RecSys 2014 keynote, he said that recommendation systems should not try to be an oracle asking users to “trust me, you’ll love this” but rather advise users that “based on your watching title X, theme Y, actor Z, you’ll probably enjoy this.”
Neil Hunt is pretty spot on, you don’t want to be preached to. The most powerful recommendations are those you inherently trust because they reveal their underlying logic. Many systems leverage black box technology driven by complex algorithms or based on simple rules. Black box applications don’t allow your intuition to complement machine computation and result in irrelevant “You may also like” recommendations, while the basic approach feels forced and overly simplistic.
Combining sophisticated machine learning technology and intuition, Wine.com leveraged the flexibility of the Relevance Cloud to implement unique selling strategies that directly combat the pitfalls associated with black box and rules-based systems. After implementing RichRelevance recommendations across their site, they noticed that some of the unique qualities about selling and buying wine also make it slightly more complicated to recommend. For example, many people repurchase the same bottles and often purchase in large quantities; upsell/cross-sell strategies tend to recommend popular products since there really is only one product to sell – wine.
With this in mind, Wine.com began to develop strategies to address the particular nuances of their product set. Starting with a ‘Similar Products’ strategy, they offered recommendations that keyed off attributes unique to wine, like varietal and region preferences. With strategies like these and other personalization efforts, Wine.com has generated a 15% increase in average order value and $5 revenue per click [View the case study here]. Cam Fortin, Senior Director of Product Development at Wine.com shares how he implemented his own strategies in this webinar.
When it comes to what works, everyone’s path to personalization is unique. Many vendors offer canned personalization that can be simply turned on. In today’s competitive marketplace, it is imperative that you are empowered to build a relationship with your shopper that is best-suited to your unique business and affords you the ability to test and implement creative personalization tactics. You need to innovate with agility, which is why we brought tools like “Build Your Own Strategy” to retailers like you, eliminating the need to wait on someone else to do the work for you.
Creating the most personalized experience possible requires adherence to one simple principle: respect the shopper. A modern personalization platform should give you the control over your recommendations to deliver experiences that are unique to you and respectful to your shoppers. With an open platform technology, you’re able to analyze and activate your own data in real time to develop more relevant recommendations that drive higher engagement, stronger relationships, and ultimately, revenue.
Contact us at personalize@richrelevance.com to learn how you can bring human intuition into your recommendation strategies.
Are your recommendations as mysterious as a magic 8-ball?
It’s time to rethink your recommendation strategies.
A modern personalization platform should give you control over your strategies to deliver the right upsell and cross-sell opportunities. You should be able to analyze and activate your own data in real time to create relevant recommendations that drive higher engagement and revenue.
Black-box applications don’t afford you the opportunity to use your own data to articulate clear strategies. Instead, you’re stuck with static “You may also like” recommendations that are sterile and lack transparency.
Consider an agile, flexible approach that gives your team the tools to tailor each strategy to reflect your customer data and brand promise. We have put together a webinar on Building Your Own Recommendations to help you learn how.
In this webinar, Cam Fortin, Senior Director of Product Development at Wine.com, will share how they built their own, highly effective recommendation strategy that resulted in 15% increase in average order value and $5 revenue per click by utilizing the "Build your own strategy" offering within the Relevance Cloud™.
Join us to learn how you can translate your brand promise into tailored customer experiences.
WEBINAR DETAILS
Build Your Own Recommendations
Thursday, March 19, 2015
9:00 a.m. PST / 4:00 p.m. GMT
ABOUT THE PRESENTERS
Cam Fortin
Sr. Director of Product Development, Wine.com
An e-commerce industry veteran, Brad Cerenzia has more than 15 years’ experience as an innovator, designer and engineer working at companies like Amazon and Redfin. Currently, Brad is the Director of Data Innovation at RichRelevance, introducing proofs-of-concept with top retailers eager to establish themselves as market leaders in adapting personalization to such areas as mobile shopping, sales associate on-floor tools, fitting room technology, POS marketing, cross-channel data technologies and assisted personal shopping.
Jolie Katz
Product Marketing Manager, RichRelevance
Jolie Katz is the Product Marketing Manager for the Recommend and Discover products at RichRelevance, creating and delivering go-to-market assets that drive demand and generate pipeline for the business. Prior to RichRelevance, Jolie worked in the Consumer Insights division of the Estee Lauder companies, where she was responsible for analyzing global market and consumer trends to deliver strategic recommendations and insight to a broad range of internal departments. She received her BS in Organization Leadership from the University of Delaware.
Lancôme, leader mondial du secteur des produits de beauté, propose une personnalisation en ligne ses clients. La marque innove par la possibilité de construction complète et sur-mesure de son look, à partir de ses produits cosmétiques.
Lancôme s’est associée à RichRelevance pour élaborer cette innovation digitale. Ainsi chaque client peut utiliser les produits cosmétiques Lancôme pour personnaliser son look, selon ses préférences et l’expertise de la marque. Le site propose ainsi des produits en fonction du teint du client, et d’assortiments réalisés par ces experts.
L’Oréal-owned Lancôme has partnered with omnichannel personalisation company RichRelevance to deliver what is being called ‘a breakthrough in online beauty’.
The technology involves Lancôme’s website and facilitates a hyper-personalised retail experience. When a consumer selects a product on Lancôme’s website, they will immediately see that product applied on a model with a similar skin tone to their own.
Lancôme, the world’s largest beauty brand, has partnered with RichRelevance, the global leader in omni-channel personalisation, to deliver a breakthrough in online beauty – a complete, personalised look curated for each shopper based on her individual preferences and Lancôme’s unique expertise.
“Lancôme is committed to constant innovation to exceed our customers’ desires,” said Alessio Rossi, VP, interactive and e-business marketing at Lancôme USA. “RichRelevance allows us to instantly combine consumer signals with expert advice on what is most flattering to individual skin tones – and show a complete, personalised look. The result is that we can now offer the same level of outstanding service and expertise online that we provide shoppers at the counter, and support a seamless customer experience at every Lancôme touchpoint.”