In the introduction to the Win/Loss Analysis in FinTech interview series, “It’s Not What You Think!“, we launched a discussion about topics including what is win/loss analysis, who it is for, why FinTech is different, and how to run an effective analysis program in that market. In this interview, Richard Case and I talk about analyzing both the reasons for winning and losing FinTech deals and why you must analyze them separately.
Dan: Richard, I think it’s pretty obvious that you should analyze lost deals for lessons you can learn. But why should you analyze won deals as well; do they contain any new information from which to learn something? If you’ve won a deal, that should mean that all of the available information has been “priced into the market” already.
Richard: When we do an analysis of prospective buyer interviews, we identify all the criteria that the buyer found important to their requirements and where they found a significant difference among the competing vendors. Some of those criteria favor the client: these are strengths and reasons for winning if the client wins. And some criteria favor the competition, and these are weaknesses and reasons for losing if the competition wins. Now, when you do your analysis, it’s critical to separate the criteria for winning from the criteria for losing. You need to keep these separate and distinct so you can advise the client on each side of the equation. Many criteria commonly appear on both sides when we analyze interviews in aggregate. For example, the solution can be a reason for losing and also a reason for winning. It can even be the top issue on both sides of the aggregate analysis. When the rep gets the solution correct and convinces the prospect that it is correct, they win. If the rep gets the solution wrong, or they fail to convince the prospect, they lose. By looking at the prospect WHY statements for wins and separately for losses, you can tease out the actions the client needs to take to be successful.
In addition, since the criteria can appear on both sides of the equation, you have to be careful not to recommend something to address the losses which negatively impacts the winning side. The client will shoot themselves in the foot.
Dan: Do you have an example of how this issue works?
Richard: Yes. Salesforce customer relationship management (CRM) is an example. When Salesforce began offering a Software as a Service CRM system, most competitors were offering on-premise datacenter CRM solutions. If you looked at a win/loss analysis back in the day, a competitor to Salesforce might have seen that their biggest strength was an on-premise, highly secure, highly performant solution. However, their biggest weakness was also an on-premise solution with all the costs of hardware and maintenance. By focusing on the on-premise features, they shot themselves in the foot and lost out to Salesforce.
Dan: Thinking back to your study that compared reps’ vs. customers’ opinions for why deals were won and lost, how did you then handle the issue of separating the criteria for winning from the criteria for losing, to advise the client properly? It’s not intuitive that the same criteria can appear on both sides, win and loss, but affect the outcomes differently. Wouldn’t the sales reps involved in the deal have exposure to this issue?
Richard: If you depend on losing sales reps to give you input, you won’t learn the real reasons for losing. If you implement changes based on this misinformation, you’ll waste tons of money. Listening to the winning reps is much more informative but you need to discount what they say about pricing and the strength of the competitors.
[For more on the sales rep vs. the customer view, see Mindreading: Why Not Just Ask the Reps?]
Dan: Ok, but does that mean that wins and losses typically have the same factor? For example, when you win, you win on price; and when you lose, you lose on price? Or, do wins and losses typically have different factors, for instance you win on price and lose on product features?
Richard: It very much depends on the client’s market. Sometimes price is very important in a commodity market where there is little difference between solutions. In markets where there is differentiation, the rank order of the criteria in losses and wins can be very different. If the market is very value-added, price can be quite low on both sides of the analysis.
Dan: I think most FinTech solutions in electronic trading are presented as a new concept, or a new paradigm. But in fact, this market is an established market. With noted exceptions, competition is really at the commodity level. How does that make a difference?
Richard: Take, for example, a deal involving multiple database vendors. It’s a commodity sale: the features are the same. So, you get other issues that factor in the buyer’s decision – like what platforms do you support, what latency; and often, it’s more about price. The features aren’t relevant.
However, for security software, those are more differentiated, so the features are important. And you can charge more. Thus, the impact of price on winning and losing falls in relative importance. And the winning and losing reasons can be in a different order. This is why it’s important to show both wins and losses separately in an analysis.
Dan: Yes. And further, when FinTech is used to support the buyer’s “secret sauce,” as is often the case, nobody wants to disclose what they’re using. When a customer buys a back-office automation solution simply to reduce the costs in a part of the business that doesn’t make or break their own differentiators, buyers might divulge more. But when a customer buys a front-office solution to support revenues or unique trading strategies, as in a differentiated execution management system, or an algorithmic trading solution, they don’t want to let “the street” in on what they’re using. This makes win/loss analysis a particular challenge for solution vendors. It’s difficult to get feedback particularly on the wins. This results in the inability to make the distinction between winning and losing factors.
Richard: Yes. This is why win/loss interviews should be anonymous and blind wherever possible, meaning confidential interviews. This is important because it elicits the truth.
[For more on non-blind interviews where required, see Win/Loss Best Practice #1: Confidential Interviews]
Dan: In my FinTech interview experience, respondents initially tend to be distrustful, even of promises of anonymous and blind interviews. And once a respondent is satisfied that their individual and company name will not be published or identified in any way, then the reluctant FinTech person might speak. Whereas otherwise they definitely would not. Even when they do speak about their secret sauce, they only do so in general terms.
Richard: That’s the problem with most win/loss analyses, which rely on non-anonymous introductions. The main reason to do it that way is that it’s easier for the win/loss vendor. But that doesn’t get to the truth. And therefore lacks credibility. If you can conduct anonymous and blind interviews, and distinguish between your winning and losing factors, then you can present both sides to the stakeholders. In fact, have the winning sales rep present the analysis results. It gets attention and has credibility.
Dan: Thanks Richard. Studying wins and losses really is a problem of asymmetry. You need to study both sides carefully.