Call tracking tells marketers which campaigns, keywords, and channels generate calls.
That’s important stuff to be sure, but, call tracking can gather MUCH more in-depth data than that.
Call tracking measures critically important, deep marketing metrics.
What follows is a list of 5 marketing metrics that marketers should be measuring…metrics that can only be gathered with call tracking. Some of these metrics, in fact, can only be gathered with our Conversation Analytics engine.
What does a lead cost? If you’re spending $500 on Adwords each week, how many calls does that $500 generate for you?
Let’s say that number is 100 calls. Well, then your CPL is $5.
Or, on the other hand, if you spent $1500 on a direct mail campaign and it only generated 100 calls, your CPL is $15.
That’s vital VITAL stuff to know as you make future marketing decisions.
Marketers typically gather that data for online marketing efforts, but for some reason many neglect it for phone leads.
How much does it cost to acquire one customer. If you spend $500 on that Adwords campaign each week, how many customers can you expect from those efforts?
5 customers mean that your CPA is $100.
Is that good?
It depends on what you’re selling. If you’re selling tires, then a $100 CPA is great because you’re likely making $400 on the initial call.
A good rule-of-thumb is that if your per customer revenue is higher than your CPA after 3-4 months, you’ve got a good business model.
What percentage of calls end up resulting in sales? This data is vitally important.
Because it can frame your sales training needs, your hiring, and even your firing.
What if Jim’s close rate is consistently below 20% and Mike’s is consistently above 70%? Or what if calls generated via PPC keyword group A are closing at 80% and calls from PPC keyword group B are closing at 50%?
Again, this is all data you can and should use to optimize your marketing efforts.
Your PPC campaigns generated 567 phone calls yesterday. That’s great. But how good were the leads?
Conversation Analytics (which is in private Beta) can track that.
Maybe your PPC campaigns only produce an average phone lead score of 48%, whereas your direct mail generated leads produce a phone lead score of 87%.
This data can go tell you, with precision, which campaigns are producing good calls vs. great calls vs. bad calls vs. junk calls.
Why is this important?
Well, data from Google and case studies from Convirza indicate that some campaigns produce junk calls up to 60% of the time. You should probably know which campaigns these are.
How do we measure if it is a good call or a bad call?
Conversation Analytics actually tracks what happens on the call itself. Convirza uses speech recognition to gather data about what was said on the calls–everything from sales readiness and buying propensity to pricing sensitivity and DM qualifying.
This is an entirely new metric encompassed in the Conversation Analytics release.
Conversation Analytics can tell marketers if there was a missed opportunity on a call. A missed opportunity could be anything from a poor sales performance by an employee, to a bad lead, to a failed opportunity to upsell.
Conversation Analytics can tell whether a call was a missed opportunity or not. This data can, of course, be aggregated to provide missed opportunity data per sales rep, marketing campaign, or even keyword.
Imagine being able to generate a missed opportunity report from a specific marketing campaign and then being able to call all those leads back and fix the problem. We’re talking about substantial revenue gains
What’s a missed opportunity worth to you?
That depends on your industry. If you’re in the auto dealership world, a missed opportunity is a big deal. A call might be worth $30,000 or more.
Long story short: you need to gather missed opportunity data. Convirza is the only tool in the world that actually analyzes what happens on the call to deliver accurate missed opportunity data.
If you’re not measuring any or all of these metrics, you’re not making fully-informed marketing decisions. You have a blind spots.
I don’t like blind spots.