Value propositions sell products, not features, so let's examine a data driven method for improving your value propositions and product marketing.
Features don’t sell products. Value propositions do. Granted, the features are the means to value and keep me around, but no one ever bought a car because they wanted a giant hunk of crafted metal. They bought it because they wanted a faster way to get from point A to point B (or to compensate for something).
Yet, we suck at marketing value propositions to our prospects.
Inundating someone with messaging is not an effective way to market. Instead, the value propositions should be tight, focused, and ultimately customer based. To help you avoid these pitfalls, let’s look at some good examples before giving you a data driven method to getting your value props right.
It's Gotta Come from Your Customers
Take a look at BufferApp and HelpScout’s home pages below. What do you notice or rather what don’t you notice? You don’t see a ton of messaging in some version of a 1999 web 1.0 site. Instead, you see exceptionally simple messaging that tells you exactly the value you’ll receive in the product. Help Scout even goes as far as to let a prominent customer tell you what you’re getting into with their software.This raises the most important point of this post: Customers and prospects are the only ones who will be able to tell you your product’s value to them. You can try to figure this out in a roundabout way or by looking at usage data. Yet, like most aspects of building a product, you’ll need to talk with your customers.
That being said, you need a process you can implement ASAP to get the right customer data quickly and efficiently. We’ve found with our customers and ourselves the following steps work best: 1. qualitatively narrow the scope of value proposition possibilities, 2. collect data to see exactly what your customer’s are thinking, and 3. segment the results out to compare and contrast how you’ll need to shape your marketing funnel.
Narrow the Scope
Theoretically your value propositions could be anything from A to Z. In reality though, your value probably encompasses at max three to four concepts from the customer’s perspective. Even so, you could test everything quantitatively using some of the methods discussed above and below, but speed is paramount. Your product, marketing, and customer are all shifting rapidly, meaning this project can’t take months, as it will be time to test everything all over again.
To circumvent analysis paralysis, start qualitatively. We recommend talking qualitatively with ten different customers and active prospects (five each). Sit down with each of them for 20 to 30 minutes and ask them exceptionally open ended questions about why and how they found you, their actual use of the product, implementation, and most importantly, what was the impact of the product’s use on: 1. them personally, 2. their department/org, 3. the company as a whole, and 4. their end user/customer.
I guarantee you will hear a number of themes emerge from these conversations. There may be three common themes. There may be twelve. Either way, write these themes out on a final sheet. You’ve just finished the hardest part of the process.
Ask in the Right Manner
Once you have the boiled down list of possible value propositions, it’s time to test things out. You could create twelve pages and A/B test, but you probably don’t have the traffic for statistical significance and you’ll take too much time. A/B testing on low traffic sites is best used when you’re testing drastically different things (and if you think you aren’t a low traffic site, take a look in the mirror, you probably are).
To get our answers quickly, we recommend utilizing surveys. Surveys?!? Yes, surveys. The reason you might be apprehensive is because 85% of surveys out there in the market are set up improperly and ask the wrong questions. For instance, imagine if I asked everyone to rate our list of eight value propositions on a scale from 1 to 10. Seems like a good idea, right? Wrong. You get results that look like the data below, where there’s no way to truly tell that proposition 1 is better than 8 because they’re so close together on the scale.
Instead, you absolutely must force respondents to make tradeoffs between options by asking them which choice(s) they value most and which choice(s) they value least. This is known as MaxDiff or Conjoint Analysis (which we’ve improved upon with one of the Price Intelligently tools included in our software). The results will look very different, and you can clearly see that proposition one is more important than proposition eight in the graph below.
Fire up a campaign and send this out to your customers and prospects with the value proposition choices from step one. You don’t need to use PriceIntel’s software or any software for that matter. Just make sure to force the respondents to make a decision and tradeoffs.
Segment the Responses
Once the responses start rolling in you’ll notice that the aggregate results are super helpful. Yet, you probably don’t have just one customer persona (if you think you do, you should read more on developing your customer personas). You need to properly segment these results, which involves simply breaking down the respondents on a number of axes.
We recommend comparing current plans, churned vs. active, prospect vs. current customer, age of customer, and any demographic characteristics you actively track (number of X, price point, etc.). You’ll notice some pretty scary and invigorating differences in how your customers think.
Repeat the Process
The only task left to do is act. You’ll now have pretty clear paths to what each of your personas care about and how to market to them more effectively. Enjoy the higher conversion rates, but remember that this data and customer analysis decays over time. You should be testing this out each time you make a significant product change or reach a new quarter, whichever comes first.
To learn more about the pricing process, take a look at our Pricing Strategy ebook