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SmartData Collective > Uncategorized > Accurate Sales Forecasting: 4 Secrets
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Accurate Sales Forecasting: 4 Secrets

thamina
thamina
5 Min Read
secrets to accurate sales forecasting
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There’s something you need to know about forecasting: the forecast is, by nature, imperfect. But this is the part where I have to walk a thin line between encouraging you not to expect perfection and discouraging you from accepting errors or just flat-out guessing. Sales forecasting is incredibly important to every organization, and though you will never get it perfect, you have to get it right.

Here are the four secrets to accurate forecasting that will give you reasonable revenue expectations and achievable sales goals:

There’s something you need to know about forecasting: the forecast is, by nature, imperfect. But this is the part where I have to walk a thin line between encouraging you not to expect perfection and discouraging you from accepting errors or just flat-out guessing. Sales forecasting is incredibly important to every organization, and though you will never get it perfect, you have to get it right.

Here are the four secrets to accurate forecasting that will give you reasonable revenue expectations and achievable sales goals:

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secrets to accurate sales forecasting

#1. Snapshotting Data

Historical data is critical to an accurate forecast. If you take a snapshot, so to speak, of a KPI on a given day and archive it, then you have that dataset always available to refer back to.

Salesforce (SFDC) is a great tool to keep you up to date on sales stats and activity, but it only tells you what’s going on now. The report you pull today will be different than the one you pull tomorrow. I keep track of regular data sets so that I can always compare them against each other—in my role, I use Domo to keep the pulse of our current efforts, as well as snapshots of monthly data to discover trends. For your organization, the timeframe may be different, but the principle is the same.

Snapshotting against the original data set is critical for accurate forecasting.

#2. Trending

Every product or service has a life cycle. The starkest example is Christmas tree sales—they come out in October (sometimes September), and then they are non-existent by January 15.

Most products or services, however, are a little more subtle. If you have a long-term product or service, I recommend gather a minimum of 3 months (or one fiscal quarter) of data. You need that much data to comfortably forecast the next month and predict future business. If your product or service has been around for more than a year, keep year-over-year metrics close by.

There’s no way to get an accurate read on your business without closely identifying trends.

#3. Real-Time Data Streams

At Domo we’re all about real-time data streams. I know real-time seems almost out of place with discussions of snapshotting data and discovering trends—but real-time data is critical in making adjustments to the forecast on the fly.

Real-time data gives you information on what works and what doesn’t in your sales pitches, emails, and marketing support. Every aspect is tested and refined so that you don’t spend any more time than is absolutely necessary discovering what works and what needs to be replaced.

Real-time data also gives you a good read on closed deals, how much you have in each stage of the pipeline, and where your sales are as compared to your goals. Without real-time data and course corrections, you could find yourself running up against the end of the month or the end of the quarter missing your forecast. And that’s never a good thing.

#4. Mature Sales Force

At the end of the day, you need to trust the people out pounding the pavement for your company. A mature sales force gives you people with enough experience under their belts to know what the “real deal” (no pun intended) looks like. They know the difference between someone who is being nice on the phone versus someone really on the cusp of buying.

You can accurately forecast with a mature sales force, because you have confidence in their commits, and you know they will get the job done. All the market potential in the world does nothing if you don’t have a team that can close on it.

What are some of your best forecasting methods? I’d love to hear about them, so leave a comment!

TAGGED:data streamsforecastingreal-timesales
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