Plan for the Future with More Accurate Forecasting

[Raihan8]

Clean data makes for a better prepared, more organized company. It allows you to run more accurate forecasts, better share information between disconnected teams, and put your company in a position to make better data-backed decisions.

Many marketing and sales departments forego in-depth forecasts because of unreliable data. No one wants to make predictions or make large-scale decisions based on data that might be misleading.

Collecting data and failing to clean it is simply leaving money and critical information on the table.

For an accurate forecast, you need to do two high level things:

Create opportunities. Companies with poor quality data may have many potential opportunities floating out in the void — unidentified, and therefore, unactionable.
Track opportunities. For forecasting to work, sales reps need thai phone number to enter data about the progress of their engagement, stages they reached, expected close date, opportunity amount etc. This requires accurate data that is correctly formatted.
In a simple forecast model you give each stage a probability and multiply that by the expected deal amount, and then use the expected close date.

For example, when you schedule a demo for your software product, the deal probability increases might increase to 20%. For a $10,000 deal with an expected close date of 12/31, a simple forecast calculation might look like this: 20% x $10,000 = $2,000 for 12/31.

But what if you have incomplete or stale data? For example, which opportunities do not have “close date” populated? Or that the “close date” is in the past? What about opportunities who have had the deal amount change as sales reps begin to learn more about the prospect?

More advanced models may factor in things like:

Number of contacts are associated to the company. How many people are involved in the process? The more contacts, the more likely it is moving in the right direction.
Last activity date. If there is no activity for the contact it decreases the probability of the sale closing.
Engagement from decision-makers. There may be many people involved in a deal, but ultimately it may come down to a final decision from a single, or a small group of decision-makers. Ultimately their level of engagement may play the biggest role in the likelihood of the deal closing.
For an accurate forecast you need reps to enter data. You also need a tool that surfaces the gaps in data or inconsistencies in that data. Then you can take them into account, point reps in the right direction, and improve time prioritization by focusing on the most impactful actions.

Speaking of impactful actions..