Scoring leads is a great way to make sure that your sales team is working the leads that show the highest propensity of becoming a customer.  And while your sales is sure to appreciate that, they will likely need a little bit more.  This is an ideal area for your marketing, sales and analytical people to put their heads together to create something that helps everyone to be more successful.

First of all, let’s take a quick trip down memory lane:

In Part 1 of this series, we looked at the data you need for lead scoring.

In Part 2, we outlined the process and approaches for calculating the scores.

And in this part, we will look at how to give the sales team a leg up with those great leads.

A Score Doesn’t Tell the Whole Story

If a Sales Rep is calling down a list of leads, a score doesn’t really tell them anything. In most sales scenarios, the rep needs a way to begin a conversation.  A score doesn’t help with that very much.  Let’s listen in on a sales call…

“Hello Mr/Ms/Mrs Prospect, this is Mr/Ms/Mrs Sales Rep.  I was wondering if you’d like to buy a widget today?”

“Why would I want a widget?”

“Because you scored 73.8.”

Click.

“Did you hang up, or did you just say ‘click’?”

As you can see, in spite of the Sales Reps savvy usage of the “Mr/Ms/Mrs” title and mentioning the numerical score, it really didn’t help win the business.  The Sales Rep ideally needs something more significant to bring up in the conversation.

Add Score Insight

Scores are calculated based on data that is in your customer relationship management (CRM) or other marketing data warehouse system.  Putting the reason that the prospect received their score into a visual format is a great way to give the sales rep some additional ideas on how to connect with the prospect. Below is an image of how this might look for one lead record. 

Items in green are positively correlated to the customer making a purchasing decision.  Items in red are negatively correlated.  In other words, the fact that the prospect hasn’t made any purchases within the last 3 months significantly lowers the chance that they will make a buying decision now.  This, however, is more than offset by the fact that they have visited the website within the last 30 days and that they did make a purchase within the last year.

Now when the Sales Rep calls, they have a much better idea of how to start a conversation with a customer.  “Hello Mrs. Brown, this is John with Company XYZ, we’re following up with folks who have visited our website in the last 30 days with some special offers…”  Wow!  I’d be a lot more likely to buy something from that call than I would from the earlier one, wouldn’t you?

Combine with Training

Remember that some of this information may be private.  If it is confidential to the customer then, of course, it shouldn’t be displayed at all (and, in some cases, it shouldn’t even be allowed to be a part of your scoring calculation – be sure to work with your legal or compliance team to be sure you’re on solid ground).  Even if you do display the data, however, be sure to train your sales team in how to be sensitive to this when speaking to the prospect.  Here are a few examples:

What not to say: Although you have 1 child at home under the age of 18, you shouldn’t let that stop you, because you’re between 35 and 50 years old so that means you want to buy a widget.

What to say: We’ve found that our loyal customers who have a young family really get a lot of value out of a widget.  Does that describe you?

And, as a general rule, I’d stay away from even bringing up what they’re currently watching on TV.  That just freaks people out.

Review

Congratulations, you’ve come a long way!  Your marketing team invested a lot of time and money into generating those leads.  You took it to the next step by scoring them so that your sales team would work the very hottest of the hot leads, and now you’ve added some context to those scores so that your sales team is better equipped to engage them and win the business.

Now that you’ve come so far with lead scoring, we’ll have a final blog on some other interesting things you can do with your new found knowledge about scoring and statistical modeling.  Stay tuned!