Ecommerce Social Networking

I'm a Facebook user.  And I've clicked the "like" button.  But I don't think I have ever done it for an ecommerce site, not even the ones who are trying to lure me with freebies.  According to a recent eMarketer article online merchants love Facebook's like button.  I think they may be distracted by the latest shiny object.  As social tech guru Brian Solis wrote in Business Week yesterday, "too many companies are diving into social media without thinking a project through."

In Brian Solis's new book "Engage" he states that likes "facilitate the sharing of 'the love' in byte-sized actions that reverberate through social networks, resulting in a formidable network effect of movement or diversion.  It is the digital curation of relevant content that binds us contextually." 

True, all true.  And for the things that I happen to be passionate about personally, I'm a big liker and I love getting turned onto other things that my network likes.

But for me, these have yet to be online merchants.  Online merchants are not going to make themselves relevant to me or know what I want if they rely solely on my liking them. 

Brian Solis also mentions in his book that we are "faced with an increasingly thinning state of continuous partial attention (CPA)." What this means for me is that I am already pretty saturated regarding where I am willing to actively participate, even something as small as a like.  I've Yelped, I've posted reviews on Amazon, but I am increasingly less motivated to do so.  So what does this mean for online merchandizers?  Namely one thing-- while engaging with people on Social Media and offering opportunities like reviews and ratings is a wonderful thing to do,  don't leave out the lurkers and the window shoppers. 

Measure engagement with everyone. Adapt your online experience to suit the current needs of everyone, likers and non-likers alike.

There’s been a lot written on this blog and in the media about how e-tailers can increase sales by tapping into the collective wisdom of their site visitors to optimize the customer experience. While the role that manufacturers play in the online retail channel is pivotal, their vantage point has has been missing from the majority of industry articles and blogs focused on this topic.  This is mainly because manufacturers have been relatively uninvolved in ecommerce strategies for the most part – until recently. Proctor & Gamble’s entry into direct sales through their eStore earlier this year reinforced our belief that the business concept of collective intelligence does not just apply to e-commerce companies.

P&G’s eStore was prompted by a mediocre year in online sales for the consumer goods manufacturer. According to a recent article by Andy McMains of AdWeek, less than one percent, or $500 million, of P&G’s $79 billion in global revenue last year stemmed from online sales via sites such as walmart.com and amazon.com. Through the eStore, P&G hopes to learn from consumers how to better market their products and improve online sales across all e-commerce channels. One of the main goals of this initiative is for P&G to learn about consumer buying patterns and share this customer intelligence with its retailer partners to boost sales.

eCommerce is unique in that Websites allow retailers to quickly identify consumer shopping patterns, and automatically adapt their merchandising programs based on this insight. This is simply not possible in brick-and-mortar stores. With Baynote’s technology, for example, retailers such as Urbanoutfitters.com and Bluefly.com are able to more quickly recognize even the most unexpected trends, such as consumers purchasing two seemingly unrelated products, and then personalize product recommendations in real-time. This improves the next shopper’s experience, builds loyalty and boosts sales.

Since most products are currently sold via retailers rather than directly by manufacturers, manufacturers are often left in the dark on the valuable data that their retail partners can obtain about consumer behavior. While brands have been able to utilize the Internet well to engage with consumers via email marketing, social networks, online product reviews, and a slew of other activities that require their explicit feedback, they have not had a direct link into the less obvious but often more telling data that ecommerce affords. This includes leading, often termed “weak” signals about consumer intent that can only be gleaned from the online shopping experience. Think clicks and hovers, not hard transactions.

This new online environment should enable P&G to monitor and respond to shifting consumer trends in real-time, and we are looking forward to seeing how their customer engagement initiative will change the overall online retail landscape. We predict that the insight gained from eStore will improve both indirect and direct sales, as P&G will be able to better collaborate with their distributers on why certain products are selling well, and how to improve upon the merchandising and online sales strategies. If managed well, the P&G eStore should also allow the manufacturer to bring innovative new products to market significantly faster based on real-time visibility into the online browsing behaviors of their customers.

The central focus of Gartner’s Symposium/ITxpo this week in Orlando is all about implementing what they’ve recently dubbed as a “pattern-based strategy”.

According to Gartner, a pattern-based strategy “provides a framework to proactively seek, model and adapt to leading indicators, often-termed ‘weak’ signals that form patterns in the marketplace.”  For the past several years Baynote has been committed to helping companies identify these patterns with technology that lets them tap into the collective intelligence of customers visiting their websites. This is something that transactional based systems such as business intelligence (BI) and complex event processing (CEP) simply haven’t been able to deliver. Here’s why:

1) For years BI, CEP (more recently) and other related technologies have helped organizations become much more efficient by automating their interactions with customers. However, in the process of creating huge economies of scale, they forced companies to lose the “mom and pop” touch that consumers expect when they walk into a local hardware store or restaurant. In failing to create digital mom and pop experiences, online retailers and publishers have placed unnecessary emphasis on promoting popular products and content, thereby losing out on profits to be gained from merchandising their long tail products.

2) In addition, these so-called “predictive” applications have historically prioritized the wrong set of indicators, often identifying consumer trends weeks, if not months, after the fact. For example, e-commerce transactions lag other more relevant indicators, such as online comparison shopping, by months. Only by tapping into the power of the collective is it possible to see early signals, spot trends and develop strategies around them before your competitors catch on. This holds particularly true for long tail products. Our customer US-Appliance tapped into the implicit behaviors of its website visitors to merchandise colored washers/dryers months before Home Depot and Best Buy began promoting similar products in their stores.

In Gartner’s recent report, entitled “Introducing Pattern-Based Strategy”, they view “the collective” as being critical to developing a pattern-based strategy. We couldn’t agree more with their position:

The collective comprises individuals, groups, communities, mobs, markets and firms that shape the direction of society and business. The collective is not new but technology has made the collective more powerful — and enabled change to happen more rapidly. The explosion of social software has enabled groups and individuals to rapidly form and rally to a cause — often resulting in significant societal changes.

The result for business is a cacophony of rapidly evolving demands, expectations, inputs and transactions, as well as an opportunity to not only react, but to seek signals of change from the collective. Market trends, some subtle, others strong, are masked by noise, and many enterprises are failing to proactively detect the patterns they rely on to direct future strategy and support investment decisions. In addition to failing to detect these patterns, enterprises are not utilizing new resources to proactively seek signals of change nor do they understand their power to influence individuals and communities.

Val Sribar, group vice president of Research at Gartner, sites Amazon’s and Netflix’s use of recommendation engines as good examples of organizations leveraging collective intelligence to support their pattern-based strategies. Sribar agrees with Baynote that recommendation engines identify new patterns in behavior as customers browse and purchase. While Amazon and Netflix are highly popularized cases, we’ve helped hundreds of other well known brands tap into their collective customer networks to significantly increase revenue through cross-selling and upselling, and higher customer loyalty.

We’re excited to see Gartner take a leadership position on this important issue and look forward to working with them and our customers to bring best practices related to collective intelligence to the forefront of modern business strategy.

It’s pretty hot right now to start corporate Twitter accounts and Facebook pages as a way be more “social” and in touch with the crowd.   But they are no substitute for a website where you can find what you need. 

My mom had an issue with Comcast recently.  I suggested she contact them through Twitter. Their Comcast Cares persona has become pretty legendary.  But my mom isn’t on Twitter and unlikely to join so I tweeted for her and she got amazing service as a result.  It was great!  I felt social!  I felt powerful!  But really I was one squeeky wheel who happened to know about how to leverage a particular channel, Twitter.

What about the more invisible, average visitor to Comcast or anyone else’s website?  What about the person who leaves disatisfied with their experience without leaving any sort of explict feedback?  What do you learn from that person and how can you leverage this to make the experience better for the next customer?   Without my tweet, my mom would have just been an upset unknown customer, searching but not finding. 

Don’t get me wrong.  I love Twitter.  My friend’s love Facebook.  But my mom and the big silent majority are still out there, searching on traditional marketing, eCommerce and support sites for answers.  Let them help each other find what they need.   Harness their successes and their failures without making them have to actively participate in anything.   By including everyone, you really are tapping and sharing the broadest possible “social” community, both active participants and average browsers like my mom.