Using Data Intelligence to Drive Social Commerce

  |  September 5, 2012   |  Comments

Social offers brands access to a real-time focus group of their customer’s interests, actions, and behaviors. The information is all there for marketers to interpret and extract value.

As the summer closes out, let’s pretend for just a minute that you’re in Paris. You’re a fashion brand marketing VP. It’s a beautiful day and you’re at the top of the Eiffel Tower watching all the Parisians and tourists below. Because you’re a marketer, you’re undoubtedly thinking at some point about the different groups of people below and how they might look in your styles and how can you best reach them and convert them into customers.

That bird’s eye view is akin to the customer view a brand can get from e-commerce analytics.

Shopping started out as a social activity – going to the mall with friends and talking about what looks good. Then came e-commerce and the social component was eliminated. Now we have s-commerce and social commerce analytics, bringing social back in a different, but more insightful manner.

Instead of imagining your customers from afar, think more about being right in the store with them, having a real-time conversation while they hold up the shirt. That’s the detailed customer intelligence social user engagement and commerce can provide when used properly. It’s an often overlooked advantage of the newest phase of social media marketing measurement.

This is an important distinction for marketers who want to keep up with the fast speed of direct response and commerce through social networks.

F-commerce (Facebook commerce) was just the beginning. As Facebook and other social networks open their data to allow action-specific targeting, and as more ad executions take place on newer social networks (Pinterest, etc) social commerce is creating a bigger, richer data set for brands to make decisions from.

E-commerce and standard audience targeting packages give brands a substantial amount of data on demographics, Internet behavior, and purchase behavior. But social commerce intelligence will add activities, interests, media consumption, and brand affinities.

With s-commerce that little boutique where a 25-year-old man is looking in the mirror at himself in a red polo shirt becomes a focus group – one run and revealed by data.

How much data? Facebook recently revealed some level of an answer to that question. According to TechCrunch, Facebook now:

  • Processes 2.5 billion pieces of content and 500+ terabytes of data each day.
  • Pulls in 2.7 billion “like” actions and 300 million photos per day.
  • Scans roughly 105 terabytes of data each half hour.

What does it mean? A recent McKinsey report on big data suggests:

…we are on the cusp of a tremendous wave of innovation, productivity and growth, as well as new modes of competition and value capture—all driven by big data as consumers, companies and economic sectors exploit its potential. But why should this be the case now? Hasn’t data always been part of the impact of information and communication technology? Yes, but our research suggests that the scale and scope of changes that big data are bringing about are at an inflection point, set to expand greatly, as a series of technology trends accelerate and converge. We are already seeing visible changes in the economic landscape as a result of this convergence.

Social commerce is part of this convergence. With social engagement and commerce intelligence brands and retailers can inform more critical decisions, with richer data sets. Let’s look at three.

1. Distribution Channels

A recent CMO Club survey found that social data is being used by agencies (50.9 percent), marketing research teams (45.6 percent), and marketing communications (45.6 percent). A significant proportion of CMOs are sharing social data with a diverse array of teams, including brand management (59.6 percent), sales (36.8 percent), customer experience/web design (36 percent), and product management/development (35.1 percent).

With that kind of depth, companies can easily generate intelligence around not only top line product sales by channel, but they can find out why one channel performs better than another.

Online retailing is driving more information than sales. Using social commerce can help brands determine the best channel to support with inventory and media spend.

2. Competitive Success & Failures

The great thing about social intelligence is that Coke can see Pepsi and Pepsi can see Coke.

Now bring in s-commerce. Competing retail brands can have visibility into what their customers are watching, buying, and reacting to.

If low prices are driving your competitor’s customers, maybe that means you have to take a different tact. Social intelligence takes out the guesswork.

3. Product Design & Promotion

Suppose a cooking brand sees that its social commerce conversions are coming directly from food blogs, or that its customers are much younger than they thought and watch TV even more than they thought. Such insights will lead that brand to make smarter choices on the products it promotes, the promotions it launches, the off-social media it buys, and the posts and tweets they send out.

Social intelligence helps marketers ensure their efforts are socially relevant and effective, driving more sales and fostering stronger customer relationships.

Conclusion

Social intelligence offers brands unprecedented access to a real-time focus group of their customer's interests, actions, and behaviors. The information is all there – right now. New tools are constantly emerging that can splice and dice this daunting amount of data and extract and deliver actionable intelligence. Marketers need to move fast and take advantage of these capabilities to strengthen their businesses.

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ABOUT THE AUTHOR

Dilip Venkatachari

Dilip is CEO and co-founder of Compass Labs. He previously led Google's mobile ads business and ran PayPal's risk and fraud management, financial services, and compliance. Dilip has co-founded and led two successful start-up companies -CashEdge and CommerceSoft - after stints at McKinsey and Goldman Sachs. Dilip has an MBA from the Harvard Business School, M.S. in electrical engineering from Rice University, and a B.Tech in electrical engineering from the Indian Institute of Technology, Madras.

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