Am I doing it right? How to evaluate spend performance (part 1)

Am I doing it right? How to evaluate spend performance (part 1)

There are a lot of marketers and companies that prioritize things like “brand” and “product” and prioritize ad spend and trade show spend, and everything looks great. Truly beautiful. Breathtaking! And when you ask for basic performance metrics (cost per acquisition, cost per conversion, etc), you get a blank stare. 

Horrified yet? Well, on top of that horror, you’ll often find that these initiatives cost tens of thousands or hundreds of thousands of dollars. “We need to be there!” cry the sale people. And they’re right. Kind of. 

Seeing companies fall by the wayside tracking metrics has always baffled me. And this isn’t just the small fish; event fortune 100 companies don’t always properly plan and execute their marketing initiatives, designing the experience with the end in mind (a conversion). Let’s not follow in their foot steps. 

Our goal is going to be to find a way to measure every single initiative we undertake, down to the smallest detail possible. Afterall, how do you know that your work is working if you don’t have a way to connect the dots and see your spend and the real impact it has. 

To tracking spend performance properly, it really needs to be done in tight conjunction with sales efforts. I mean, I can go out on the street and get a hundred leads for the product, but if sales can’t qualify them, they’re basically garbage (I’ll tell you in a little how to survive in an environment where you can’t do this). 

So, that means the unsung champion of a marketing/sales organization is the CRM system. Done properly, the CRM system should give your company all kinds of insights into every aspect of the marketing and sales process. Done improperly, well, you can still get some information, but you need to be really careful (a poorly conceived CRM system can throw out false positives in a lot of different, dangerous ways). 

The objective here is to connect your efforts as closely as possible to sales outcomes, and there are basically two ways to do this: lead source and mixed attribution. Lead source is originally how marketing connected their efforts to sales, with each activity passing leads through that sales would then “convert” to an opportunity if they could move the lead along the interest path. For the snappier brains in the audience, you may already see the problem; what do you do with the duplicates? Yes. For smaller markets (highly segmented B2B markets), there’s an extremely high likelihood that you will have the same person (or entity, if you want to get into the ABM conversation) interact at multiple points along your marketing funnel; not only have you seen this person at a trade show, and on a webinar, but they’ve also downloaded your e-book, and have submitted a couple of web forms. 

Pop question: which marketing initiative is responsible for this conversion. Surprise: all of them! (Or double surprise; none of them. The customer is buying from us because the sales guy had a great conversion in the hotel lobby after the event. Bazinga!) This kind of confusion can lead people to think that marketing attribution is meaningless. Please no! Please, please, sweet, please, no. Event basic-bitch lead sourcing is better than no attribution at all. But the real magic happens once you have your body of metrics tracking for a period of time, and they’re mostly reliable. What you can do at that point is multiple linear regression; while a bit esoteric, this style of analysis will help paint a picture of which lead generation sources work best together, which, when you really think about it, is really how marketing works. 

So to sum up, track your lead attribution the best way you can (multiple is preferred, but you can probably general a “multiple” result from a single source if you keep your data clean, and don’t arbitrarily delete stuff). Once you have it tracked, and connected to sales, even if you only have the simplest attribution source, you can still evaluate them individually in terms of which contributed to how much sales, and make better decisions from sales.

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