Don't Let Your Sales Team Drown in Big Data

Taming the big data beast has become one of the greatest challenges in B2B marketing and sales, growing in proportion to the surge in social media and the Web. In B2B, as well as B2C, everyone is online all the time. The potential for big data to amplify targeting and outreach is huge, but the reality is that using the available insights requires both art and science, especially in sales and marketing.

The data that's out there is plentiful and readily available, and technologies such as search engines can allow your organization to access and view hordes of it. The challenge is separating the wheat from the chaff—identifying the data and insights that actually help find and understand potential customers, rather than that which just creates noise—and then providing this to your business in a way you can use it.

This is a marketing challenge first and foremost. Yet many marketers just dump a score and a seemingly random set of data onto the sales team to sort out, as though gathering the data is the end, rather than a means to an end. The sales team ends up with lots of unconnected, often irrelevant, data. They spend a great deal of time trying to find needles in a haystack, and more often than not, still have to go look for new data themselves with other tools, such as Google. Naturally, this puts marketing and sales at odds, frustrated and pointing fingers over who's to blame for missing sales targets when they should be working together like a well-oiled machine.

The best solution we see is a simple one: Start with an idea of the "ideal customer" you are looking for, identify the core metrics that define that customer at both the company and individual level, find that data from across the entire Web, build a profile, and then improve this process over time.

While this process may sound challenging, complicated, and time consuming, it can be done. Most leading marketers take five simple steps to get started:

  1. Narrow your focus. If you are buying a new phone, you don't start by looking at every phone out there. You know what size, OS, and price range you want, and then use this information to narrow down your choices. In the same way, when searching for customers in the sea of available data, start by working with sales to identify the characteristics and behaviors of your best customers and focus on potential new customers who match those criteria. Use data and statistics to improve these models, but don't give in to the "black box" model, where you need a statistical sample set and three months of analysis before you can even start.
  2. Don't forget that companies are collections of people. While understanding which companies to target is important and often easier, it is people or groups of people who actually buy. In large organizations, there are usually many groups and teams with different needs. Getting down to the individual level, informed by the company characteristics, allows you to not just score a lead, but also to find new leads that fit a similar profile.
  3. Always use accurate and up-to-date data. Data has a life span, and it's getting shorter every day. The world is moving faster, and the prospect who came to your conference last year or read an article four weeks ago has probably moved on. It can take just one out-of-date engagement to land you an unsubscribe for life.
  4. Make meaningful connections. Use the relevant data you've gathered to reach out with context. Telling prospects why they're receiving your content ("I saw your comment on that article, so I thought you might be interested in this..." or "Since we both attended that same session at the conference, you might find this helpful...") creates a connection far faster and more meaningful than a cold call or email with zero context. Data without context is not much more helpful than just noise.
  5. Find the right tool to enable the process. Getting a handle on big data doesn't change the fact that it's still big. You'll need a demand-gen solution that can handle the size and scale you need, align it to predictive analytics, and also provide an end-to-end solution to streamline the process.

Finally, once you start getting results, don't stop. This is the beginning of a journey to get better over time, build an ideal customer profile for every product and buyer to whom you sell, and forge a whole new relationship between sales and marketing. Together, and with the right tools, you can harness the sea of data out there to find new customers.

Doug Bewsher is the chief executive officer at Leadspace, an SaaS lead generation company. Previously, he served as chief marketing officer of both Salesforce.com and Skype.

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