A good marketing plan is based on deep customer understanding – who they are, how they view solutions and how they buy. That said, I’ve never built a marketing plan that wasn’t based on at least a dozen different things that I didn’t know and simply had to assume were true. Early in my career I didn’t worry too much about those assumptions as long as I had marketing tactics that seemed to be working. Until they stopped working. Then I worried about them a lot. Now I find I spend a lot more time exploring what my key assumptions are up front and then looking at what clues my metrics give me about how those assumptions might be refined or shifted.
Here are some examples:
Target buyer assumptions – You might have assumptions about who your target buyers are. For example, I’ve built programs aimed at business buyers where we made an assumption that IT would be largely in charge of the purchase and would be the budget holder, while line of business folks were merely influencing the purchase. One of my campaigns – a combination email and inside sales call-out campaign showed that business buyers were increasingly becoming the budget holders and we needed to shift our list building efforts, programs and tactics. At another company we assumed that buyer persona’s in one vertical were similar to those in another. After a couple of fairly unsuccessful campaigns was discovered that smaller companies in the new vertical used completely different job titles and we were often targeting the wrong person in the organization.
Messaging/Offering assumptions – You will often have assumptions about what customers think are the most important features of your offering and how they describe the value of those features. These are likely to shift over time as not only your product evolves but also your competitive landscape evolves. For example I was once marketing a graphing tool for developers where our biggest advantage was the large number of different types of charts we supported. However at one point our largest competitor got close to us in terms of the number of charts they supported and what we assumed was our key differentiator didn’t seem all that different any more. Going back to our customers however revealed that our assumption wasn’t exactly correct and that they were interested in having many different kinds of charts but the flexibility in being able to customize them was really where the value was.
Buying cycle assumptions – you might assume that a purchase goes through a certain process and then later your sales data might indicate something else is happening. For example at one B2B startup I worked at we mapped a sales process that included approval by purchasing as the final step to a deal. Legal teams might be involved but we assumed that they were largely driven by purchasing and weren’t a significant step in the buying process on their own. This was true – but only for smaller companies. As we pushed into larger companies we were seeing increasing legal involvement and started creating materials to address the common concerns that came up when our contract when to a prospect’s legal group.
how did you discover that different job titles were used?
i.e. did you have a target response rate for the campagin, and when it was evident there was something wrong, did you get on the phone to those people on your list, or did you physically go there and assault them “why didn’t you respond?!!!!”
what seems to work when you need to follow up with prospects to learn what went wrong or right? do you need to use incentives to get them to spend time talking with you? or is it just a numbers game were you keep calling until you connect with someone? what kind of a sample size do you need to determine if your findings are accurate?
Good question. In the case of the titles being wrong, we started to see our inside reps being directed to the other title when they called into larger accounts. Then we called up a couple and figured out there was a difference in the way they were organized. Later when we looked at our web sign ups we saw that title too but it was inside sales that noticed first.
I’ve never incented folks to talk to me, I’ve just kept calling and emailing them. I find it helps if you make it clear you aren’t in sales 🙂
The question about sample size is a good one. My experience has been with B2B companies where we were generally dealing with smaller number of customers. My rule used to be that if I heard the same thing a handful of times, I would add it to the list of things I would regularly probe on (I.e. it made it on the assumption list) and then if I confirmed it with another handful of customers and there was a clear pattern, I would stop asking about it until I saw something that would make me think things may have shifted.
That might not sound very mathematical but most of my issues weren’t something I could use a survey to tease out.
so persistence works, but probably including in your message that you have something to offer that they value may also help you get connected?
and i’ve just read in Running Lean that you only need about 5 people to get 85% of your information, so this i proof it’s true. thanks!
April, you’re obviously a better professional because you’ve learned from some of your failures. (Sometimes I don’t!)
Under messaging assumptions: Sometimes clients assume that the feature is what people are interested in, rather than the benefit. Which pretty much tracks your example. My advice is to always understand the benefits that people desire or require, and the emotions that are attached to them, if you want the message to be as strong as possible.
Edited to add: Thank God your blog comments has an “edit” feature to clean up the tpyeos.
It’s always easy to get tripped up on the features versus benefits thing. The other problem is getting stuck on benefits that might have been important once but just aren’t anymore.