Laying the Groundwork for the Sales Data Revolution

If you were hiring for a sales pro in 1982, you might have looked for qualities like grit, focus and an ability to connect with others. Find someone like that and you probably had yourself a solid sales rep. But today? Today you need someone with all of those qualities and something more – the ability to translate data into insights.

No, it’s not as easy as checking someone’s degree on their LinkedIn profile. But you need that ability on your team just the same. Skip that essential requirement and you may well hire someone who doesn’t speak the same language as your buyers. Remember, data is a kind of universal language; while the types of metrics used will vary from organization to organization, depending on goals, the patterns revealed by measurement will always point reliably to certain conclusions.

Obviously the ability to collect and interpret data has been a powerful tool for sales teams. Information that would have taken months to compile is now at our fingertips in moments. It’s the IT equivalent of moving from a horse and buggy to a Tesla.

And just like a powerful car can help you win a race, relevant analytics are proving the ultimate competitive advantage. Just as marketers use marketing automation to target their buyers with unerring precision, sales pros can now understand their leads and refine their approach without a degree in data science.

So what’s the drawback? (You knew there’d be some kind of obstacle.)

Change. You can’t pour new wine into old bottles. These new tools and new analytics need new systems, more efficient processes, different skills that turn engagement data into tailored communications.

With that in mind, take a look at the 3 steps you need to take to lay the groundwork for the data revolution.

1. Clean your database
Picture your contact database. It’s probably like an old closet, full of incomplete contacts, duplicates and outdated information. Not only does that junk data slow down your team (and frustrate them to boot), it costs you money by delaying what could be a faster and more profitable sales process. You want your reps talking to real prospects, right?

Solution: clean your data. Use an outside resource like a data validation firm to verify phone and email information before your next outbound campaign. And it doesn’t stop there. Make sure your scoring system makes sense, with behaviors like replies and content consumption ranked accurately as indicators of interest. Messy data equals time and budget squandered.

2. Standardize your messaging
Here’s a mistake many teams make: they diligently measure the above-mentioned behaviors without realizing that the leads are responding to divergent messaging. To really understand a customer’s favorite content, top challenge or preferred communication medium, you’ll need results based on consistent, standardized messages. Without that unification, you won’t understand what’s performing and what isn’t because too many variables are in play.

Work with your marketing and creative teams to ensure all content reflects unified messages. Then make sure everyone has access to the same measurement-driven insights.

3. Align your communication strategy
This is another area where you can’t afford any randomness. How you communicate matters as much as what you communicate. Will you call the prospect or email? Will you use live chat or a form with customers? What cadence and frequency will you use to reach cooling prospects?

Whatever you decide, the key part is standardizing those processes across the sales team. Yes, you want your reps to flex when that’s called for. But they must be operating from a consistent foundation. Automation can help with this, such as setting a predetermined number of emails or calls, right down to delivery timeframes and offers.

If thinking about these dynamics makes you feel overwhelmed, be aware that you don’t need to build digital Rome in a day. Follow the above steps for small batches of data. Decide on the top messages that seem to be having an impact, implement them across the team, and start measuring. Create a simple workflow per lead and measure its performance. Then keep repeating these steps until your data is healthy, robust and accurate. Along the way you’ll improve your own data-fluency – and you’ll be that better positioned to steer your team to success.