So you’ve launched a product… Is the product selling? How’s ASP (Average Sales Price) after discounting, and is the discount larger than you expected? Deal size? Cost of sales? Are there measurable predictors for lost opportunities exiting the pipeline at each stage? Are there ways to accelerate the wins through the pipeline or increase the number of them? If your license is per term instead of perpetual, is your product getting renewed? Are you getting multiple terms sold in advance? Are you hitting all of the customer’s addressable surface or are they just trying it out in a small patch?
And if your product is one of many… are your wins correlated with the wins for other products? What would happen if they were bundled? Does your product cannibalize something else the company sells? How would you know? Do ELAs hurt or help your product’s adoption?
Companies ask these questions because they need to manage the business. Tautology, right? So let’s be blunt: you can’t get investment or spend investment without some way to predict how you’re doing, and you can’t decide if you’re going to continue an investment if you can’t see how that investment is performing. As a product leader, your paycheck is coming more or less directly from that investment and these questions have a ring of immediacy to them.
And if your product is a consumer-facing direct sales widget, you may be facing some mysteries (aren’t we all), but the numbers are probably relatively clear. Unless it’s sold through retail partners. Enterprise software sales though… when your product starts at “new car” and can cost up to “Central Park penthouse”, measuring sales performance starts getting strangely difficult.
Enterprise software is sold to customers who don’t always want to be clear about how much they are willing to pay or when they are willing to pull the trigger. At the very least, this means that the deal data is unclear and may change for reasons that don’t involve your product.
Enterprise software is sold by sales people, and sales people are maximizing their compensation plan and pipeline. At the very least, this means that entering the data you want into Salesforce is pretty low on their priority list. At the extreme, it can mean a variety of bad behaviors, particularly if the sales person is not actually competent. They might have good reasons for sandbagging deals or inflating pipeline, or they might have heard it was a good idea somewhere and misunderstood the reasons… but all sorts of craziness can happen in an enterprise sales team.
Setting aside the truly bizarre behavior of a failing team, sales leadership might try a bunch of mechanisms to deal with the normal lack of clarity. Favorites include:
- Dedicated people who force the deal to make sense. They might be called something like “sales operations” or “deal desk” or “contract specialists”, or the function might be overloaded onto an inside sales team. The resulting organization is simply fatter than before, because there’s still customers and salespeople with their own motivations and context in between the data and the organization.
- Punitive policies: the deal won’t be booked or the sales person won’t be paid if all the reporting isn’t done in a correct and timely fashion. This is an amusing game of chicken because the company willing to a) not sell product or b) risk a lawsuit over a principle of report quality has got their priorities seriously backward. Actually going through with such a threat is a great way to lose customers and sales people, which really reduces your sales numbers.
- Rewarding policies: the sales person will get a toy or points toward the yearly club or public recognition for doing their reporting in a correct and timely fashion. Again, simply amusing, because this data is not worth an incentive large enough to motivate a sales person worth hiring. A good sales person in enterprise software makes very large amounts of money. You can play on their sense of camaraderie and you can ask them to be diligent, but those factors are present without the incentive. In order to incent, the prize has to mean something in relation to their compensation, and that number is not small. Furthermore, the sales person’s job is to make the customer’s organization complete the purchase, and the incentive has no impact at all on the customer. Is it supposed to make the sales person work harder? Then why isn’t it simply paid to them as part of their total compensation? Is the incentive for the customer’s purchasing department? Sorry, that’s illegal bribery.
Given the ineffectiveness of these interventions, why do companies pursue them? Any generalization will miss a lot of examples, but I am fond of two explanations: the manager who is more comfortable with spreadsheets than conversations, and the manager who isn’t sure what to do, so they do something that they understand.
So we return to thinking about what the deal data is worth… there’s a quote popularly attributed to Charles Babbage, “Errors using inadequate data are much less than those using no data at all.” If the data in Salesforce can be considered directionally correct but untrustworthy in detail, it is still useful for the purposes listed above. You can manage with it. You’re working with a string and a rock instead of a titanium yardstick and a laser level, but a lot of buildings have been erected like this. Improving the quality of your sales measurement tools is worth very little when compared with double-checking their results: after using the spreadsheet to form questions, talking about specific deals with sales people and customers can be remarkably illuminating.