Put simply, “Predictive Analytics” is the act of analyzing data in order to predict buying behavior. It’s a tool that sales and marketing teams can use to reduce CAC and sales cycle length. The idea is simple: if you can get to someone right before they buy, you’ll save time (and money). In this post I’ll explain how to use Predictive Analytics to close more customers this year.
A couple weeks ago my ex-manager and mentor wrote an article on LinkedIn that put words to something that’s been in the back of my mind for the last two years of my life. I had an “Ah-ha” moment. An epiphany. As I read the article, I realized I’ve been thinking about sales outreach all wrong.
The article introduced the concept of behavioral data. Have you heard of it? I had, but I wasn’t thinking about the power of this concept in building an ideal customer profile, prospecting, or writing email templates. In the next 1,300 words, I’ll deconstruct what behavioral data really is (with examples) and then explain how you can use it to grow your business or hit quota.
Behavioral data is a tool you can use to identify buyers at the right place, and right time. If you’ve ever done sales before, you’ll understand that it’s all about context. Have you ever sent a cold email and received a response like this?
Michael, Great timing. We’re evaluating lead generation companies right now. Are you available tomorrow at 9am?
If so, you’ve experienced the power of behavioral data — most likely by happenstance and out of sheer luck. The goal of this article is to take the uncertainty and luck out of the equation and start building predictable outreach strategies.
What is Behavioral Data?
There are two types of data that marketers and salespeople generally think about.
Demographic data: This is data that describes static characteristics of a business. In other words, these are data points that don’t change frequently. Examples of this include: company location, industry, number of employees, etc. Think LinkedIn advanced search.
Behavioral data: This is data that is subject to change frequently. Whereas demographic data describes what a company or prospect is, behavioral data describes what it has done. In other words, behavioral data describes events that a company or prospect has triggered.
This is all getting a little complex and MBA-y for the internet, so I want to take a step back and provide an example.
A couple weeks ago someone came to me with a problem. Let’s say his name is John and he sells a product called Circle (a competitor to Square). Well, John’s problem is that 99% of the time he emails or calls a small business they tell him they are happy with their point of sale solution.
In his pitch, John tells them, “Square is great, but if you are a chef who runs his/her own business, you need Circle. We’ve built it for a very specific use case.”
99% of the time the small business owner responds, “I’m not a chef, and I already have Square.” Even the best salesperson in the world would have a hard time convincing these prospects to switch. John lost the game before he ever stepped up to bat. He has 99 problems, and they are all data.
I spoke with John for about 30 minutes and asked him some questions about his business. We determined that his ideal prospect is not only a “chef who runs his/her own business,” but a chef who has just opened up a restaurant. These are prime prospects because they haven’t purchased a point of sales system yet.
When we determined this, he had an idea, “Everyone that opens a restaurant is listed in state business registries. What if we prospected those?”
That’ll do! Opening a restaurant is a perfect example of behavioral data (a prospect has done something that we can call an event)
“And Yelp descriptions generally say whether it’s chef-owned. We could search there.”
Perfect! Rather than just call everyone that opens a restaurant we could do some research to see if they would even benefit from Circle. Remember, he’s built his product for a very specific niche, and it’s important we try to reach that niche.
“Oh and there are chef magazines that talk about recently opened restaurants.”
Now we’re talking! Not only would this prospect be a perfect fit, we’d even have a reason to reach out.
In just 30 minutes, John and I were able to go from Spray and Pray, to targeted outreach. As an entrepreneur this makes all the difference. John doesn’t have time to call and email 99 people in order to find a single prospect. He also doesn’t want to feel like a cold calling telemarketer. Pairing behavioral data with demographic data makes him a targeted sniper rather than a heavy machine gunman.
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Alright, back to the good stuff!
How to apply this strategy to your business:
Redo your ideal customer profile
If you aren’t using demographic and behavioral data to define an ideal customer profile, do me a favor and print your buyer personas out. Then walk from the printer to the window. Create a paper airplane out of the paper and send it as far away from your building as possible. It’s time to rethink ideal customer profiles.
The world of spraying and praying, interrupting innocent family dinners with cold calls, and selling to people who don’t want your product are over. The internet has enabled a new era of sales outreach. Rather than pick up a phone book, or a list from Data.com, and start dialing, the entrepreneur or saleshacker would be wise to target his or her outreach. Remember, we want to be a sniper, not a heavy machine gunman.
Go and find out what your equivalent of John’s list of recently opened restaurants is. Maybe it’s surfing LinkedIn for VPs of Marketing who recently joined a company. Maybe it’s Crunchbase’s list of recently funded companies. But I guarantee your ideal customer is not simply mid-size businesses in California.
Build an account/prospect list
Use a combination of demographic data and behavioral data to actually find a list of your ideal customers. This may take some creativity. Ask questions like “Where are my customers hanging out online?” LinkedIn can be a great source of demographic data. But finding behavioral data usually requires going a step further.
If your ideal customer uses a certain technology, try checking out BuiltWith or Datanyze. If they publish news events or PR releases are your trigger, consider signing up for Google Alerts or Mention. Look into state business registries.
I spoke with an entrepreneur recently who wanted to target property managers with elevator maintenance contracts. Elevators have to be inspected yearly by the city which they reside. So he files an Information Act request for $15 and gets a CD of all elevators that need inspection. Every request yields him a highly targeted list with 3,000 leads for $15. Not bad, huh?
Write targeted messaging and hybrid personalize
Get creative in the way you reach out to prospects. Don’t write them an essay. Keep it short, sweet, and personal. Tell them why you are reaching out to them. Then tell them what you offer (in two sentences or less). And finally, make a direct ask (e.g. “Do you have time for a phone call on Tuesday?”) But take it a step further and make use of your new ideal customer profile. Mention the behavioral event in your email. When John reaches out to chefs he writes this:
If all goes according to plan, Carl will respond, “John, great timing. That time works. See you soon.”
Consider using hybrid mail merge tools like Close.io, Outreach, PersistIQ or Cadence to speed up this workflow.
Test, test, test
Email 250–500 prospects and then review the data. Use your mail merge tool to track positive response rate and optimize for that. Change your subject line if the open rate is low. Change your ask if the response rate is low. And be religious about tracking the data. If you think tracking data is too much work or too difficult, start out simple!
Set a goal of testing one new profile every month. This is enough time to run prospects through an entire outreach cadence and then review the results. Test new messages to the same profile, and then the same message to different profiles.
After you’ve used behavioral data to crush your sales goals, give me a shout! I would love to hear how it goes 🙂
This post was originally published on the Close.io blog. If you’re a startup, check out their CRM!