“Customer Propensity To Buy”

For those people deep into analytics and understanding (usually) consumer buying behaviors, the concept of Propensity To Buy, is not new. It’s been around for decades.

Propensity to buy is simply about determining the liklihood of a customer buying something. We use it in developing our websites, our web ad strategies, our marketing programs, and all sorts of things. The goal is to identify that moment and set of conditions (product, place, price) that a customer is most likely to buy.

While the propellerheads, try to develop propensity to buy models with 5 decimal points of accuracy, this concept is important to everyone in B2B sales–though without the 5 decimal points of accuracy.

None of these models is perfect, but they help us more effectively target customers that are more likely to have a need for our products/solutions now, as well as forecast their likelihood to buy.

This topic came up in a query about my post, How To Forecast More Accurately. A follower wrote about his company’s forecasting process. He described it, “We look at what stage the deal is in, it’s probability, then there’s a little bit of guesswork.”

When I replied the only meaningful indicator was the customer propensity to buy, he was shocked. He had never heard of the concept, his current company and no other company he worked for had ever had that concept as part of their forecasting process.

Sadly, what he describes is what is common to many sales organizations and forecasting processes. We focus on where we are in the process, we measure our progress with a probability assessment, then we add our opinion to whether it will close or not.

All of this focusing on what we’ve done, where we are at, in our selling process. It has little connection to the customer’s likelihood of buying (propensity to buy).

As we are looking at forecasting, we need to address two things:

1. What is the likelihood the customer will make any buying decision by a certain date?
2. What is the likelihood they will select us?

If we are doing our jobs and working with the customer well, the first question can be answered with reasonably high accuracy. By this I mean:

1. We’ve helped the customer create a high sense of urgency by identifying and quantifying the impact of doing nothing.
2. As a result of (1), they have established a date for when they must have a solution in place.
3. We have helped them establish a plan that enables them to make a buying decision and have a solution in place by the date established in (2).

This issue, helping the customer answer the first question, is probably the most critical issue around propensity to buy. It is the most important issue/challenge our customers face.

We know customers struggle with buying, we know they have constantly shifting priorities, attention gets diverted. The research shows 53% of buying journey’s end in No Decision Made.

We don’t know what percentage of buying decisions are made when the customer originally targeted a decision, and what percentage have slipped. I suspect the majority slip quite substantively.

As a result, understanding the likelihood a customer will make any decision and the date they intend to make that decision is critical–both for them to know when they will start seeing results and for our forecasting.

The second issue is a little more difficult, but not a lot. That is, What’s the likelihood that when they buy, they will buy from us. We never know for sure until they give us a PO.

But, in my experience, customers will give honest feedback, particularly if we are working with them, as we should, rather than “peddling.” They will share what they their preferences and our positioning–it’s actually in their self interest. They want to make the best choice possible, so the want to make sure each supplier knows where they stand and is doing their best to help the customer solve their problem.

We always tilt the odds in our favor, if we are the people working with the customer, helping them navigate through the buying process.

We also get a more refined assessment when we break their choice down into smaller choices. Rather than, “Do you prefer us or the competitor,” we might look at, “For these specific sets of issues, which solution do you feel more comfortable with?, and “For these different issues, which solution……” (Some of you will recognize this as a SWOT analysis we conduct with our customer’s direct feedback.”

This gives us a more refined view of our positioning and that of the alternatives they are considering. (And please please please, never ask, “Whose price do you prefer?” You already know the answer to that.)

As a result, we can, if we are honest with ourselves, make an informed guess about whether they will choose us when they make a decision.

We will never be perfect when we make a forecast estimate. But like the propellerheads analyzing propensity to buy, we can make much better estimates if we look at each of these issues, discussing them openly and honestly with the customer.