USING SOCIAL MEDIA FOR B2B DATA AGGREGATION AND SALES INTELLIGENCE
The B2B sales and marketing landscape is changing in a variety of ways due to both the web and the social web. While companies are still generating leads and using some form of sales force to offer products and services to new and existing customers, more information is available to help that process. People are now publishing mountains of data everyday and making it freely accessible. While it used to be hard to get data about customers, competitors and industry, the problem now is that there is too much data and many people don’t understand what to do with it. Some of this data is personal, and might not seem relevant, but developing schemes for aggregation of data will help B2B companies understand their customers and markets.
This is not a discussion of tools to do this, but the beginning of a thought process. Sometimes we work out ideas by writing about them and this is one of those examples. I am throwing this out on a Friday afternoon to get you to start thinking about this can work in your business. This is an idea that I will develop over the next few paragraphs.
The best way to manage data is to put it in the appropriate buckets, whether that’s a spreadsheet page, database or even index cards taped to the conference room wall. With so much data, probably the only use for the index cards would be to define the buckets, and sometimes a physical representation of this is the best way to get a handle on it. So think about the kinds of data you have been tracking traditionally: sales by product, sales by customer, sales by salesperson or territory, tracking leads through the funnel to determine successful marketing tactics. Now how can that be recombined with social media data to gain a broader understanding of your market?
Start with your largest customer and find their relevant employees on Twitter or LinkedIn. Don’t just choose the marketing or sales people, but look for product managers, purchasing agents, and even finance or hr people. If this list is very large, you may want to skim it once a week, or even once a day for a significant customer. You are looking for company culture mentions, major events like expansions or layoffs, comments about new products or services they might be offering, conference attendance, even comments about competitors. This is not a quick process, but you are looking for data points that can be used as sales intelligence, but also mapped to sales data moving forward. This process will get easier, especially if you get feedback from those in the field who are benefiting from this data.
The social web data can be viewed in lots of ways that reveal other trends. What if you track all the product managers across your industry? As you skim through this data manually, or using keyword searches or monitoring tools, you will understand if your products are well-positioned based on what your competitors are working on. As a larger number of people are looking for recommendations online, if you are tracking these industry terms, you will better understand prospects’ needs. Suppose you start monitoring a location-based app like foursquare for geographic areas around your customers or competitors? See who checks in at the airport, or at that restaurant that the client always takes you to when you are in town. Compare these to your competitors’ salespeople. The more intelligence you know about the world of your customers and prospects, the better you can meet their needs.
Now that I have written through some of this, it feels a bit like corporate spying through Twitter, but it really is no different than seeing who is having dinner together at a conference. And yes, it may be a bit early in the adoption cycle to expect sales people to tweet their customer meetings, not to mention the checking in using a location based application, but start thinking about what is out there. Who tweets in your industry? Who answers questions on LinkedIn? Can you take that information and correlate to any of your existing data? Can it help the sales cycle? And don’t overlook published studies with data you can use for your own presentations, plus data in presentations on Slideshare.
This is not something that is easy to implement or expected to provide quick results, but will ultimately pay off once you can find a way to manage incorporating this data into your tracking. Please leave me a comment if this is something you could see instituting at your company, or you have ideas how to make this more manageable.