As any experienced B2B marketer knows, data quality is king. Because B2B prospect and universes tend to be smaller and better defined than their B2C counterparts, identifying the right prospects and tailoring the marketing message to their needs is vital. In other words, you’d better know exactly what your ideal customer looks like, where to find them, and what messaging they respond to. This means you need access to high-quality data.
Recent trends have exacerbated this fact. One major trend is the adoption of marketing automation technology. Witness the meteoric rise in recent years of automated demand generation tools, such as Eloqua and Marketo. During the past five years alone, Eloqua has received multiple rounds of financing, and recently announced its plans to raise as much as $100 million through an IPO. Marketing automation in the demand generation space makes sense because, when employed correctly, it can dramatically improve response rates, reduce costs and boost marketing budget ROI – not to mention nurture leads and acquire customers at astonishing rates. Moreover, it works quite literally while you sleep.
Effective marketing automation for B2B demand generation requires accurate and up-to-date business data. Think about it: what good is setting up an elaborate drip marketing acquisition program if your prospect contact details are incorrect or out of date? What’s more, lead scoring may be a highly effective tool for evaluating which leads get specific communications and follow-up… But what happens if you’re sending out these communications to the wrong type of companies in the first place – firms in the wrong industry, firms that are too small, too young, or simply don’t pay their bills on time?
This is where data quality comes into play. The way marketing automation usually works, as data are pumped into the software’s database, the marketing automation gears begin to turn and Key Performance Indicators are tracked based on the prospect’s interaction – opens, clicks, forwards, etc. – with the campaign elements. These data points are all tracked and used to calculate the lead’s score based on pre-established business rules established by the firm.
But let’s take a step back. Data hygiene should actually start before the data enter the marketing workflow. Successful database marketing means reaching out to the right types of companies in the first place. In fact, starting with the right initial data set can impact a campaign’s results more than any other single factor, including creative, offer or design. Important questions need to be asked like: “What does out best customer look like?” or “What types of firms have the highest lifetime value?” It can easily be argued that these qualifiers are significantly more important than whether an email is opened, a link is clicked, etc.
Beyond marketing to the right types of firms, having accurate contact details such as titles, emails and phone numbers is essential to success. Sure, you may have a list of 100,000 prospects that you market to each month. But how old are those records, and how frequently have they been updated? The fact is, data decay with time. Did you know that within 12 months, 66% of titles, 43% of phone numbers, and 37% of email address become incorrect? Truth be told, it’s likely your database of accurate data is a lot smaller than you think.
The next place data quality looms large is when the lead has been passed through to the sales team for follow up. This is age-old juncture between sales and marketing – the gap that solutions like Eloqua and Marketo are helping to fill. Marketing automation tools take qualified and nurtured leads, and deliver them to the sales team along with a score and contact details. This in and of itself solved a huge problem, namely connecting marketing activities to the sales process. But knowing if a lead is Hot, Warm or Cold is only one piece of the puzzle. Isn’t it just as important to know if the firm is a legitimate prospect or already a customer? This is why your data need insight.
Data insight essentially means information about data. In the B2B space, commercial data insight refers to deep information on the firm itself. Commercial insight might include, for example, who a firm is owned by or who owns it, how many locations the firm has, how many employees, annual revenue, and, just as importantly, whether this firm pays its vendors in a timely manner.
This is important for many reasons. Let’s say, for example, you get a fresh lead and you need or determine if the prospect is already a customer through a recent merger or acquisition. Well unless you have access to a tool or database that can blow-out corporate family trees, how will you know? Moreover, in lieu of a recent ownership change can this salesperson even call this lead, or should it forwarded to someone else?
In other words, commercial insight should affect how your sales team engages with its prospect in a real and meaningful way. Moreover, in today’s fast-changing environment, having updated commercial insight is more important than ever. Chew on this: through bankruptcies, consolidations, mergers and acquisitions, the corporate landscape itself can change on a dime. In fact, within the next 60 minutes, 12 companies will file for bankruptcy, and 78 new businesses will open their doors.
This is not an exhaustive list, but it should give you a good sense of why having access to clean, complete and accurate business intelligence is central to your B2B marketing success, especially if you are using or plan to implement a marketing automation solution. Got any questions or feedback? If so, I’d love to hear what you have to say.