60% of customers will shake their head NO to a sale up to 4 times before they actually say YES to it. Sadly, many sales reps miss their opportunity to get the YES when 48% of them don’t do the necessary follow-up.
And when they do the needed followup, it’s driven by such things as intuition, geography, account size, the customer’s job title, or their position on a call list or spreadsheet.
Should we be surprised when only 42% of salespeople expect to meet (not exceed) quota?
What is a salesperson to do?
It’s time you replace your dart board with a crystal ball. Introducing predictive sales analytics—the strong arm of sales artificial intelligence that automatically and continuously analyzes customer behavior for buyer signals and readiness to buy.
This isn’t science fiction. Most of your customer behavior, from their inbox and phone activity, to their sales cycle length and content preferences, have valuable data-driven insights that you no longer have to sift through.
In addition to improving your chances of closing more deals, predictive sales analytics also improves the customer experience by delivering the right engagement, with the right content, at the right time, every time. Customer expectations are higher than ever before, so now is a perfect time to read this blog post and use the readily applicable practices—and close more deals!
Read on to learn more about predictive sales forecasting and how it can help your sales teams and their sales performance.
60% of customers will shake their head NO to a sale up to 4 times before they actually say YES to it. Sadly, many sales reps miss their opportunity to get the YES when 48% of them don’t do the necessary follow-up.
And when they do the needed followup, it’s driven by such things as intuition, geography, account size, the customer’s job title, or their position on a call list or spreadsheet.
Should we be surprised when only 42% of salespeople expect to meet (not exceed) quota?
What is a salesperson to do?
It’s time you replace your dart board with a crystal ball. Introducing predictive sales analytics—the strong arm of sales artificial intelligence that automatically and continuously analyzes customer behavior for buyer signals and readiness to buy.
This isn’t science fiction. Most of your customer behavior, from their inbox and phone activity, to their sales cycle length and content preferences, have valuable data-driven insights that you no longer have to sift through.
In addition to improving your chances of closing more deals, predictive sales analytics also improves the customer experience by delivering the right engagement, with the right content, at the right time, every time. Customer expectations are higher than ever before, so now is a perfect time to read this blog post and use the readily applicable practices—and close more deals!
Read on to learn more about predictive sales forecasting and how it can help your sales teams and their sales performance.
What is Predictive Sales Analytics?
The key to predictive analytics is data. Companies with access to today’s technology are swamped with data. Often there is so much data they don’t know what to do with it.
The beauty of predictive analytics is that it leverages artificial intelligence, or AI, to analyze customer data to predict future sales outcomes. These data-driven insights use both historical and stored data, such as CRM and engagement data, along with statistical algorithms and machine learning to push these predictions to your sales force.
The science of this idea is not all that new, consider the work of casinos and sports betting, for example. Yet, how it can shape selling for your company can be revolutionary for you. By taking that massive volume of data you have at your fingertips and inputting it with big data techniques, predictive analytics has become even more accurate.
The real outcome of predictive analytics is to go beyond understanding what’s happened in the past to getting a good assessment of what’s likely to happen in the future.
Why is the Data so Important?
It’s not new that data is important for a sales force. It helps you to know things about your customers.
What have their preferences been in the past? What can you learn about the customer from this data?
Sales are so often about fostering the relationships between the customer and the salesperson. If the salesperson is working hard to get their foot in the door or convince the customer to give your company a try, then the more they know about the customer the better.
Yet, the data is historical, it tells about the behaviors of the past. AI for sales uses historical data to help your sales force get predictive information for the future. When your sales team can anticipate the needs of the customer as they are about to come about, what they can do is more powerful and creates statistical results.
How to Use Predictive Sales Analytics to Drive Sales
Have you gone on your Amazon account only to find that Amazon already knows what you’re thinking about buying? Or look at a product to buy and then Amazon helps you find more related options?
Amazon has used the information it has about you as a consumer to predict what purchases you might make in the future. Predictive analytics can provide the same kind of information for your sales force.
Predictive analytics takes the data you already have on hand and helps guide your sales force to understand the future needs or wants of your customers. What will they want? What will they need? When will they need it? How can you as a company be the ones to meet those needs?
Let’s take a closer look at the wide range of applications of predictive analytics
Sales Forecasting
Predictive analytics has a powerful impact on sales forecasting. We’re not just talking about the fact that it reduces the need for lengthy, “Where is it?” sales meetings? We’re talking about predictive analytics’ ability to anticipate future sales, helping the team and company overall scale up inventory, promotions, and even more sales staff at the right time.
Furthermore, your sales team is enabled to anticipate when and how to close future deals. When using predictive sales software like Veloxy, salespeople can drill down into the necessary dashboards and reports to see the upcoming buyer signal notifications and guided selling recommendations. For the sales manager who wants to still conduct sales meetings, this is a huge boon for their productivity.
Lead Scoring
Traditional lead scoring tracked surface-level metrics such as email opens and clicks, form submissions and downloads, and call pickups and times. While these metrics still have some value, it pales in comparison to account based metrics, multiplier metrics such as repeated engagements in a short time frame, and tracked metrics across multiple platforms.
While you may be getting nervous considering the amount of time that manually scoring customer behavior across your CRM, marketing automation, and sales engagement platforms will take—don’t fret, predictive sales analytics takes care of that for you, further improving the efficiency and productivity of your sales team.
However, if you’re data is larger or more unique than most, be sure to work with your IT department on preventive measures related to lead scoring.
Lastly, using predictive sales analytics for lead scoring helps discover new and better buyer personas, furthering your chances of closing more deals.
Pipeline Management
Predictive analytics also works to improve your sales pipeline management. If you have a salesforce managing a large base of clients and customers, the information provided from the AI will allow them better control of where a customer is in the pipeline.
The AI helps predict the potential for future revenue. It also helps to analyze where the customer is in the sales process and address potential problems.
It also works to help the sales manager with sales forecasting, predicting future sales slumps or growth, too.
One important feature of AI is its ability to help your salesforce understand the average time it takes to flip a lead to a customer who is making purchases.
Lead Nurturing
The sales process isn’t a linear one and often the time a salesperson gets in front of the customer is highly limited. So, when your salesperson has that short window in front of the customer, they need as much information as possible to nurture the lead and move the customer towards a sale.
Intent data and behavioral data can be used in predictive sales analytics to tell your sales forces exactly where the customer is in the buying timeline.
Using the data can help your sales and marketing teams know how to address the customer and what information they might need including when to send content and when to implement social selling.
Content Creation
Content creation for your marketing team is an important part of supporting the sales team. Predictive analytics takes content creation to the next level because you have a deeper understanding of the customer’s needs and where they are in the sales cycle.
With more depth of knowledge, you can have more impactful content. Content creation can know when to focus on:
Predictive analytics helps you to not only understand which customers need your product or services but also what content to use to get through to them to make the sale.
Content is an important part of the sales process. Your customer is likely to consume multiple pieces of content from a variety of sources before they’re ever ready to make a purchase.
The key is to know the customer so well that you give them the content they need to guide them towards the sale.
Predictive Analytics for B2B Sales
The benefits of using predictive analytics for B2B sales can help your company in both marketing and sales, especially in areas where your sales haven’t been reaching their full potential.
You can use the tools and big data to make educated decisions related to lead generation, marketing to other companies, demographics, and keyword selection.
Inside Sales and Predictive Analytics
There’s a case to be made on which sales team can benefit the most from predictive sales analytics—inside sales or outside sales. Let’s start by making the case for inside sales.
Sales development managers, account managers, and other traditional cold callers can suffer from immense sales pressure and mundane, repetitive sales processes. This shouldn’t be a surprise. They have to maximize calls and emails, and without predictive analytics, there more apt to miss their number than hit it. Plus, having people hang up or unsubscribe is a gut-punch to their morale.
However, with predictive sales analytics, inside sales reps can do more of what they’re supposed to do—start value-based conversations with customers, not to mention improve their open rates, reply rates, and new meetings and upsells / cross-sells.
Outside Sales and Predictive Analytics
Sales Management and Predictive Analytics
Sales managers need to guide their sales teams, both inside and outside. It’s their role to help them understand and use the wealth of information provided from predictive analytics in a more powerful way to make the sale.
Why Salesforce Users Need Predictive Sales Analytics
As a company, your salesforce is at the heart of your success. In today’s competitive job market, you want to do everything possible to find the best there is in sales and then retain them as employees.
A big part of their success goes back to the tools you provide for them as they work to make the sales. When salespeople use Veloxy predictive sales software, the data speaks for itself. Who wouldn’t want these kinds of results:
Using predictive sales analytic tools for your sales force will increase engagement from customers and the ability to convert that engagement into sales.
Next Steps: Predictive Sales Analytics
Take your sales team to the next level with predictive sales analytics. The AI technology takes the data you have and provides you with the information your salesforce needs to increase their effectiveness and close the sales.
If you want to learn more about predictive sales analytics, get a demo, or even try it with your company for free, contact us today.