A 5 Step Guide to Spotting the Data “Black Holes” in your CRM

By Matthew Menard

“My CRM is a sparkling picture of absolute truth!” —said no one, ever.

We all know our CRM systems tell an incomplete story about the state of sales operations. We know that the data isn’t always formatted properly, or that the fields don’t match our business perfectly.

But just how wrong is your CRM data? How do these inaccuracies, in sum, impact your mission-critical sales forecast? How much could your shoddy CRM data—and lack of organized metadata—be messing with your ultimate revenue?

We’ve organized the 5 most common data “black holes” we see in CRMs, and why understanding them will be key to delivering a more accurate forecast and closing more pipeline.

  1. Inactive Owners CAN Still Sell Things

    Remember when Ted got fired last week? Ted is now an “Inactive Owner,” meaning he’s been scrubbed from the CRM system, but there are still open opportunities tied to his former account. These opportunities aren’t any less likely to close just because their owner has been ejected, and yet because they have an “inactive owner,” they can no longer show up on the sales forecast. This is a counter-intuitive example of CRM data being “dirty,” simply due to the structural reality that the minute an active owner is toggled to “inactive,” the footprint of their pipeline is essentially gone too. We recommend re-assigning Ted’s deals ASAP to help close the deal and keep revenue on track.

  2. Won Deals Stay Won

    The champagne has been popped and everyone’s celebrating a major deal that just closed. But is this deal… for real? Turns out, 97% yes, and 3% no. When we analyzed this factor across all our clients, the “win rate” of won deals turned out to be ~97%. That means 3% of “won deals” become “un-won”—maybe they fall apart in legal, maybe the “win” was prematurely entered. Who knows!? But the reality is that your revenue forecast probably counts a won deal as revenue on the books. Once again your CRM data has failed you!

  3. Backdating Happens

    Everyone backdates. It’s not like CRMs are real-time 24/7 monitoring systems that auto-update based on our every thought and action. But all this backdating (entering in data retroactively, sometimes weeks or months later) has an impact on how truthful your CRM can really be. Knowing the conditions, triggers and cycles of backdating that will inevitably occur in your sales org, much like knowing the weather, will help you make a more accurate revenue forecast than if you acted like backdating doesn’t exist. It turns out that the metadata associated with backdating is supremely difficult to model and predict—unless you have artificial intelligence on your side.

  4. Listed Amount vs. Final Amount: A Tale of Two Numbers

    Do you like being caught off guard by the bill at a restaurant, or surprised by the final price of a car you’ve been looking to buy? Neither do we. Having certainty around the listed vs. final price would be nice, but this isn’t the case in listed deals vs. final deals. Typically final closing amounts for the average deal vary quite a lot from the listed value during the sales process. And unfortunately, the Final Amount is usually less than what was projected. Final deal amounts can also go up, but in general, your CRM data is going to overshoot the total amount your deals will actually close for. The exact degree of inflation is anyone’s guess—unless you have an intelligent tool like Aviso to predict (with at least 90% accuracy) the final amount of every deal in your pipeline.

  5. Listed Close Date? Simply Add 2 Weeks.

    Typical reps overestimate how quickly they can close a deal by approximately 2 weeks. To make matters worse, they rarely underestimate. This space-time-reality-bending optimism is especially pernicious when the close dates are early or mid-quarter. This time-inflation can functionally cause a domino effect, pushing the actual close date of numerous deals later and later (even into the next quarter), which could be disastrous for your forecast and revenue target. Perhaps instituting an “add two weeks” policy to all estimated close dates could curb this thorny trend? Or maybe having a tool that automatically forecasts your actual close dates with 90% accuracy would help.

Aviso exists to illuminate every dark corner of CRM data and metadata with the power of artificial intelligence, and turn that hidden information into actionable insights that raise sales revenues. Your CRM data may be horrendous, but your sales forecasts and revenue actuals don’t have to be. With the power of AI, we’re here to help.

Claim your spot today in our free trial offer (no commitment required) and see how AI can provide an unfair advantage to your sales team.

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