As analysts and brokers are clamoring to predict the next economic downturn, business leaders are permanently trying to get ahead of the curve and create predictable and sustainable growth, allowing stakeholders to know what’s coming down the road. However, given how many variables they encounter on pipeline management and sales forecasting, it’s no wonder some fail.
Data shows that 79% of organizations miss their sales forecasts by 10% or more.
Artificial Intelligence is one technology that has proven power in predicting transactional outcomes. In some cases it has been able to increase revenue by up to 30 percent for companies, just by providing increased productivity, more insights into customer behavior and suggesting actions to close business faster.
However, sales leaders are increasingly finding that AI can also allow them to produce accurate revenue projections, by offering insights into their pipeline, rep behavior and future outcomes.
InsideSales.com, the sales acceleration leader, has recently launched Predictive Pipeline — an AI sales software for managers and leaders looking to gain insight into the health of their pipeline and coach their reps towards more accurate sales forecasts.
“Sales leaders and their organizations are increasingly having trouble forecasting revenue consistently and accurately. Only 46.9% of forecasted deals actually close, and those that do– rarely close the way that was predicted (CSO Insights). This takes its toll on sales rep productivity, as they will spend inordinate amounts of time working on deals that won’t ever close,” said InsideSales.com CEO, Dave Elkington, according to a company press release.
“Using Artificial Intelligence, we can dramatically enhance human judgment when committing to sales quotas and revenue numbers. The accuracy of these predictions is much higher with AI intervention, which means sales managers are confident in sales rep’s commits, and stakeholders know what to expect at the end of the quarter,” added Dave.
Solving the Pipeline Management Equation
The pipeline management equation start with, you guessed it — people management. People are the most important variable in this equation, as they still run the sales process, which includes forecasting data. Some might think AI is taking over the world, but that’s not happening just yet.
Here’s a few things that AI can do for you, when it comes to pipeline management:
Identify Sales Superstars From Average Performers
Sales managers need to cull bad sales rep behaviors quickly when it comes to pipeline management and forecasting.
The end-of-the-quarter rush, opportunity sandbagging, over or under-estimating deal sizes are all bad rep behaviors that affect pipeline management. ‘Zombie’ deals get carried from one month to the next, from one quarter to the next, because sales reps keep thinking they will close. Other times, they might not report good deals moving through sales stages, so they can have data to report in the next quarter. All this leads to inflated pipelines and difficulty forecasting revenue.
Accurate information is the key to removing bad rep behavior and rewarding good behavior.
- First, segment your reps into performance quadrants.
- Identify the behaviors that separate one group from the next.
- Establish remedy plans and provide coaching to improve sales effectiveness.
Spot a Good Deal From the Bad
A sales rep will be happy when they’ve come across an opportunity. However, not all sales deals are created equal: there are key characteristics of a good and a bad deal. These are fairly evident by studying what has happened in the past. There’s a few cues you can look at:
- Is your sales cycle 30 to 90 days, or shorter, and what has happened to deals going over the sales cycle?
- What are the industries where you’ve won most deals in the past?
- In which region is your product-market fit best, and what’s the outcome for other regions?
- How many touches does a customer need, on average, to close a deal? Have you had success outside this average range?
- What happens with your deals if sales reps forget to follow up? What if they go too long in answering inbound leads? InsideSales.com research shows that leads called on 5 minutes after coming in are 100x more likely to connect and qualify.
It shouldn’t be hard to spot patterns like this, but the good news you don’t have to comb through your data in spreadsheets to do it. Intelligent sales forecasting software can work it out faster than you doing a manual analysis.
Once you figure out your sales patterns, you can weed out deals that never seem to die, or highlight deals that are at risk, for further evaluation.
Capture and Understand Pipeline Changes
Changes in the pipeline from one month to the next can determine whether or not a deal will close, and what to forecast. Most sales managers hold weekly pipeline review calls with reps. However, they can waste up to four hours just assembling data for analysis in Excel.
This is no longer acceptable: sales managers need to spend more time analyzing patterns and understanding pipeline changes, rather than scrambling to capture data.
Predictive sales forecasting software allows sales reps to save time, with features like:
- Automatic and continual snapshotting of all pipeline changes over any period of time (close date, pricing or probability)
- AI to inform deal scores and predictions. Combined with sales reps notes, this gives an accurate idea of how the pipeline has been adjusted dynamically
- Pivot views, so you can see your results by product, region or business unit at all times
Increase Sales Forecasting Accuracy 30%
Predictive Pipeline can increase in forecasting accuracy of up to 30%, compared to just using an Excel spreadsheet, or other sales forecasting systems.
To learn more about how top sales organizations use artificial intelligence for pipeline management and improved sales forecasting, join the InsideSales.com webinar “Running the Perfect Pipeline Review Call.”
During the webinar, Aaron Janmohamed, head of product marketing for InsideSales.com, and Scott Smith, principal product manager, will demonstrate how AI technology can solve your pipeline management challenges.