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The Migration of Web Techniques to In-Store Retail Practices

Via ralphbijker on Flickr

Via ralphbijker on Flickr

Think about the companies doing the most technologically advanced stuff. Amazon. Google.

Grocery stores.

Say what…? The place where oranges sit in piles in the produce section. Boxes of cereal lines the aisles. The frigid ice cream aisle.

Well, they’re not in the league of Google and Amazon. But grocers are more than those aisles of food and ceilings of fluorescent lights you see. Two trends in the industry borrow heavily from the advancements on the Web:

  1. Website optimization
  2. Recommendations

I’m not talking about monitors with web pages inside stores. I mean the shopping experience has been affected by these developments. Here’s how.

Website Optimization => Store Layout and Merchandising

E-commerce sites live and die by their conversion rates. A key piece of the conversion rate puzzle is effective navigation and presentation of items to site visitors. One company that helps with that is  Tealeaf, which records and analyzes visitor behavior to help site owners optimize conversions and return visits.

In a physical space, you can’t record people’s clicks and actions. Or can you?

As reported in a recent Economist article, retailers are starting to video record shoppers’ behavior in the aisles. For instance, here’s how one supermarket used technology provided VideoMining to understand visitor behavior in its juice section:

Another study in a supermarket some 12% of people spent 90 seconds looking at juices, studying the labels but not selecting any. In supermarket decision-making time, that is forever. This implies that shoppers are very interested in juices as a healthy alternative to carbonated drinks, but are not sure which to buy. So there is a lot of scope for persuasion.

These are exactly the kind of metrics that e-commerce sites track to improve their conversion rates. Use of cameras in-store to do the same thing is analogous to tracking visitors to your website.

Personalized Recommendations

Amazon.com really led the movement to provide effective recommendations to existing customers. One report I’ve seen says that Amazon derives 35% of its sales from these recommendations. Amazon’s recommendations are generated from your shopping history, compared to others via collaborative filtering. The success of these recommendations has inspired others to build recommendation engine services, including Aggregate Knowledge, Baynote, MyBuys, RichRelevance and others.

The same thing is happening in-store as well. You know that loyalty card you present to your grocer to get discounts? It’s used to record your shopping history. Historically, grocers have done little with that information. It was more of a device to keep you coming back to the store.

But in the past few years, grocers have been getting hip to the idea that their customers’ shopping history can be used to personalize the shopping experience.

Once, I was product manager for just such a system, called SmartShop. Pay By Touch’s SmartShop used a Bayesian model to compare your purchases against those of other shoppers, and determine whether you exhibited stronger or weaker preferences for a category or product than the overall average. A set of 10 personalized item discounts were then selected for you based on your specific purchase preferences.

On a website, returning customers are presented with a set of recommendations as they shop. In-store, what’s the analog? Kiosks. Kiosks are the in-store interaction basis with customers. SmartShop notified you of discounts via a print-out from a kiosk at the front of the store. This was key – get you the discounts right at the point of decision, when you’re shopping. Not unlike e-commerce recommendations.

Prior to Pay By Touch’s demise, SmartShop was getting good traction among grocers, who were looking for ways to increase basket size, increase loyalty and differentiate themselves. And it wasn’t just SmartShop. Price Chopper and Ukrops use a recommendation system from Entry Point Communications. UK-based Tesco is the granddaddy of personalized recommendations, provided through Dunnhumby.

Teaching Old Dogs New Tricks

While e-commerce benefits from being all-digital and various identification mechanisms, grocery historically lacked these. But that’s changing. Retailer have picked up the best practices of their online brethren. Things are now much more measurable and personalization is no longer the province of the online players.

Looking forward to grocers introducing Twitter into the shopping experience…

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For reference, here’s a white paper I wrote about SmartShop when I was at Pay By Touch:

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Using FriendFeed for E-Commerce

The secret sauce of FriendFeed is the development of a trusted network of referrals and commentary by users. People add users to and prune users from their subscriptions based on how well interests align. Once you subscribe to someone, you develop a good feel for their interests and perspectives over time.

This process lowers the barrier to accepting information from someone, as you learn to trust him or her.

In other words, fertile ground for e-commerce.

Seth Godin had a nice post a few months back, The truth about word of mouth. Here’s a quote from that post:

The truth about word of mouth. It’s hard. Sure, it’s hard for you. Your brand doesn’t get as much as you like. But that’s not what I mean. It’s hard for the consumer. A few people like to blab and babble. Most people don’t. They lay low, because they’re afraid or shy or just not used to talking about brands and products or experiences.

Getting people to talk about products they buy is the tough. Yet that kind if information is exactly what most of us are looking for. According to the Keller Fay Group, 80% of us trust recommendations from family, friends and influential persons over all other forms of advertising and marketing.

Think about your own buying decisions. Don’t you love it when you can get a solid recommendation on a product from someone you trust?

This got me wondering…does FriendFeed have an opportunity in the e-commerce space? Not as a direct seller of goods. But as a trusted referral network. With some added features, there’s a nice revenue opportunity riding the rails of the affiliate marketing world. And users would get better info on products.

But first let’s look at a previous effort here, Facebook’s Beacon.

Facebook Beacon: Misfiring on Three Counts

Facebook rolled out Beacon last fall. The idea is that you can broadcast your purchases from online retailers back into the Facebook newsfeed of your friends.

Well, Beacon was excoriated. Two reasons for this:

  1. Beacon’s user control and notification process were terrible
  2. People weren’t sharing a lot of external activity into Facebook, making it seem weird to have that suddenly occur

A third problem with Beacon, even for people that wanted to share product information, was that the product information passed through the newsfeed pretty quickly. If you happened to be interested in the product at that moment, great. But if you were in the market for a given product later, you couldn’t search for information about what your friends bought.

FriendFeed: All About Sharing External Things You Like

FriendFeed’s whole vibe is different from that of Facebook. You’re supposed to bring your outside interests into the site. Commentary and opinion is the order of the day. Interactions revolve around those interests, and accompanying commentary and opinion.

Why not extend that mentality to products that people buy? We already see things with a product orientation coming through FriendFeed:

  • Books: Book recommendations come through via Goodreads. For instance, Here’s a discussion around the book Spook Country. Users will also directly post recommendations, such as this one for Community: the Structure of Belonging.
  • Music: People stream in their Last.fm and Pandora music selections. What a Wonderful World by Louis Armstrong got a nice discussion going.
  • Movies: We see people’s movie tastes through NetFlix on FriendFeed. Here’s some discussion around the movie Hancock, with Will Smith.
  • Amazon: Amazon wishlists tell the world the things a user wants. Often these are books, music and movies. But a lot of interesting other products come through as well. Here’s a discussion around the Nikon D300 camera.

People are already sharing product-related stuff on FriendFeed. Which has incredibly high potential. Here’s what I mean…

Push vs. Pull Marketing

Louis Gray asked this question recently on FriendFeed:

I’ve seen a lot of stories lately around behavioral targeted advertising, and privacy. But in theory, wouldn’t you rather see more relevant ads? Isn’t this a good thing?

Many of the responses were suspicious of the tracking or didn’t think ads could ever be that relevant. Here are a few responses:

Jill O’Neill: “No. If I need to buy something, I’ll track it down on my own.”

Dobromir Hadzhiev: “I’m with @Jill, nothing beats the research, ads are and always will be annoying.”

Amanda Chapel: “Some of this stuff would make Joe Goebbels blush.”

Bwana McCall: “In my 16 some odd years on the internet, I have to yet to see an ad that I wanted to click on.”

A lot of good opinions, and they bolster the argument that making trusted product recommendations available when someone wants them (“pull marketing”) has advantages over running ads (“push marketing”).

This is why I think sites like FriendFeed, and even Facebook, have enormous potential in the world of e-commerce. They can become the source for getting recommendations and asking questions about products.

What Would FriendFeed Need to Make a Play in E-Commerce?

Say you’re an  expecting first-time parent. You want to buy a crib. Right now, that’d be a little daunting on FriendFeed. Here’s a search for the word ‘crib’. Lots of stuff there, but it’d be tough to use that for making a purchase decision.

Here are some things that would help users find products that their friends have purchased on FriendFeed:

  • An ‘Add to FriendFeed’ button at the checkout of e-tailer sites
  • A special designation of these streams from e-tailers as ‘PRODUCT’
  • The ability for users to hide all feeds with the designation ‘PRODUCT’
  • A tab on FriendFeed set up specifically for all feeds designated ‘PRODUCT’
  • Search of all ‘PRODUCT’ feeds
  • The ability to click a link on the product name, and be taken directly to that product on the e-tailer’s website

Once a user lands on the e-tailer’s site from FriendFeed, FriendFeed gets a cut of any purchases by that user, a la standard affiliate marketing agreements.

Users would get a much better way to find products they want. Just like the blog posts and articles that stream through, each person would likely specialize in product categories that fit their interests and knowledge. You would come to trust the recommendations of different users for different product categories. You’d have the person who knows cameras. Who knows home decor. Home entertainment systems. Running gear. Toddlers’ toys. Womens’ shoes. Flowers. Etc…

What do you think? Would you use such a system? I would.

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