Among the many software tools that have transformed sales teams’ lives in the past few years, Configuration-Price-Quote (CPQ) systems are standouts. CPQ applications are in place at a large majority of companies these days–83 percent, according to a report from Accenture released last year. And there are good reasons for that. For companies with standardized products and relatively simple pricing structures, CPQ can deliver fast results, accelerating quote generation and improving pricing discipline.
At the same time, CPQ is far from being a silver bullet for companies with more complex products and price hierarchies. These businesses often have highly negotiated contracts, or want to develop a deep understanding of their customers to maximize revenue opportunities hidden in their quote generation and pricing processes. In more complex scenarios, CPQ systems aren't as effective at selling into existing customers because many of those customers have agreed to discounts, pricing, and product entitlements. If companies don't have easy access to that data, then leveraging a CPQ system won't work because of two critical factors:
1. The CPQ is missing all-important historical customer pricing details.
2. These data gaps cannot be filled by CPQ alone.
The complexity of historical customer pricing data matters
Companies tend to underestimate the complexity of their customer data and the sheer variety of changes that impact it. That’s true even for large, highly strategic accounts (see my post Where is this relationship going anyway? It’s complicated.”) Let’s say you're a B2B company with complex end customers, and you’re considering a CPQ implementation. Odds are that you've done some M&A. Your product mix has likely evolved quite a bit, perhaps over decades. When you look at any given customer relationship, you may have a whole sequence of master agreements and pricing models, along with extensive documentation.
“Companies tend to underestimate the complexity of their customer data and the sheer variety of changes that affect it.”
You need that document-based information about the existing customer base to flow into your CPQ. If that doesn’t happen automatically, you’ll have to default to manual processes to reconcile what the configurator is telling you with whatever arrangements your sales ops teams have already put in place: "But we agreed to give them a 23 percent discount six months ago.” Or, “Oh, they have a special SLA.” This, in effect, dilutes or even eliminates the entire value of the CPQ system for that transaction.
Of course, it’s not just your current data and existing customer base that you need to think about. The challenge of accommodating complex and nonstandard data doesn’t end once a CPQ system is installed. You'll have custom quotes because you're getting to the end of the quarter. Or RFP-driven agreements that aren’t amenable to a standardized quote or a standardized product configuration. Or you'll have highly-negotiated relationships or “fingerprint” deals: “We'll never do another one like this, but we need to do something special to get the deal."
Filling in the CPQ data gaps
When you try to apply CPQ to these more complicated parts of the customer base, it’s all too easy to get pulled into boil-the-ocean mode. That's when CPQ projects run into 18-month implementation periods and companies spend millions of dollars trying to build out the CPQ rules. More often though, sales teams simply bypass the software in their pursuit of the more complex—and lucrative—deals; they do all the wheeling and dealing, but fall back on spreadsheets and ad-hoc processes to capture the results, again undermining return on your CPQ investment.
“When you apply CPQ to the more complicated parts of your customer base, it’s all too easy to get pulled into boil-the-ocean mode.”
It doesn’t make sense for CPQ initiatives to get bogged down in trying to fully automate the long tail of transactions that are high-value and highly complex. You get the bulk of value from your CPQ investment by automating relatively simple or standardized transactions; that’s where CPQ is most effective.
However, you can start to impact your pricing and quoting accuracy with highly complex, high-value customers by leveraging a solution like Pramata’s. That’s because we provide accurate, complete and actionable data that fills the gap in enterprise systems, including CPQ systems. Bridging the data gaps enables sales teams to tap into vital, hidden customer data in those systems.
Sales reps have all the information and tools they need at their fingertips, so they don’t need to sidestep the CPQ system to do their jobs. That means smoother deployments and better pricing discipline, which in turn means a faster return on your CPQ investment and getting the maximum value from those large, high-value, highly complex customer contracts.
You can learn more here about how Pramata turns complex contract information into meaningful, actionable customer relationship intelligence