Sales is a notoriously difficult profession. It’s hard to know which leads are worth pursuing and even harder to close a deal. That’s why more and more companies are turning to machine learning for help. The purpose of Machine learning in sales is to provide valuable insights into which leads are most likely to convert and what kind of approach salespeople should take with each one. In other words, it can make the entire sales process far less hit-or-miss than it currently is.
I personally experienced the power of machine learning in sales recently when I was working on a big project for my company. We had a huge list of potential customers that we needed to get through, but we didn’t have enough resources to call them all individually. So, we used a machine-learning algorithm to prioritize the list for us based on factors like past purchasing behavior and demographic information.
The results were amazing: not only did we end up closing deals with some of our very best customers, but we also saved an incredible amount of time by not wasting time on calls that weren’t going anywhere.
Machine Learning in Sales: Increasing Sales with New Insights
Sales representatives are always looking for new leads and ways to increase their sales pipeline and close more sales. Machine learning can help by providing new insights into customer behavior and patterns.
By understanding customer data, machine learning can help sales representatives identify new leads, create targeted sales campaigns, and predict which products or services customers are most likely to purchase.
The prime goal of this sales automation is to automate the mundane tasks and allow salespeople to focus their time on the most qualified opportunities.
The ultimate goal of selling more is to do it more efficiently, without having to invest a lot of money into hiring more salespeople.
The sales industry is currently shifting from relying on instincts to using data.
In the past, most sales activities were based on this “sixth sense” or “intuition” of a sales rep.
Although it was effective, it was inefficient. It was like running around in the fog.
When artificial intelligence and machine learning started making their way into sales teams, things changed.
Now, it’s artificial intelligence that will guide your sales journey all the way from identifying a prospect to retaining them. Without a doubt, it’s only a positive thing.
Machine learning can be used to improve various aspects of sales operations, including lead gen, segmenting customers, and recommending products.
Let’s take a look at some of the ways that artificial intelligence is transforming the sales process.
How ML Is Transforming Sales
Artificial intelligence, especially machine-learning, is revolutionizing many aspects of the business world, including in sales.
Machine learning can significantly improve the speed of your sales team‘s workflow, allowing them to focus on the most qualified opportunities.
Without sales, a company cannot grow. This is why every company has to consistently bring in new revenue.
We are pretty certain that this also applies to your business. Luckily, now, you have a new tool in your arsenal, and it is called artificial intelligence.
Sales teams that used artificial intelligence (AI) and machine learning algorithms in their sales process saw a 50% increase in their number of qualified leads, a 60-70% decrease in their average talk times, and a 40-60% reduction in their costs.
The sales process relies heavily on making accurate sales forecasts and using insights.
Unsurprisingly, then, companies who use artificial intelligence and machine learning algorithms in their sales process see their lead numbers rise by 50%, their average talk times drop by 60-70%, and their costs reduced by 40-60%.
The 2018 State Of Sales Report by Salesforce found that high-performing teams use tools to help them sell smarter and more efficiently.
1. Sales Forecasting Using Machine Learning
Machine learning is used to predict which deals will close.
Machine learning can be used to make predictions about future sales and trends. These sales predictions can be run on cloud-based or virtual machines. The written results can then be distributed through an interactive dashboard. This will provide a single truth source to the entire organization, and make reporting more transparant.
Having one source of information for your entire sales team can make reporting much more transparent.
Forecasting sales with machine learning is time series dependent.
Forecasting future sales figures is a challenging but necessary part of running a business. While there are several methods, the two most common are time series models and neural network-based systems.
2. Lead scoring
If your sales representatives are spending time on customers who are likely to not buy, then they’re wasting a lot of time.
These days, machine learning (ML) based customer relationship management (CRM) software helps your sales team identify potential customers by predicting the likelihood of conversion based on a set of predefined characteristics and traits.
After all, with all the data we have about customers, the process of qualifying them can be very effective for turning them into real paying customers.
3. Pricing and data analysis
Data analysis can help you to predict customer attrition, figure out your pricing strategy, or help you to restructure your offerings to better meet customer demand.
With machine learning solution, you can analyze large amounts of complex data very quickly. This can help you generate useful information for your business. Moreover, by using professional data generation tools and solutions, you can leverage existing data for future automation more effectively.
At the end of the day, the price you’re offering is the single most important factor when trying to make a sale. Traditionally, sales reps have to look through reams and reams of data to figure out which price point is the most likely to get the customer to buy.
Many traditional marketing techniques rely on gut feelings and instinct, which doesn’t always yield the best result.
Now, with the advent of big data, huge quantities of historical information can be analyzed by machine learning algorithms, which are capable of automating the pricing and quoting process.
4. Automating Repetitive Tasks for Sales Teams
Artificial intelligence and machine learning algorithms have automated many tasks, including making sales processes much more efficient.
Using AI, sales teams can automate time-consuming tasks like sending out automated messages and booking meetings. This frees up time for sales reps to focus on selling, networking and analyzing their sales process.
By automating your outbound sales process, you can free up your sales team to focus on pitching, networking and analyzing the data.
5. Use consumer data to your advantage
Companies are looking for ways to utilize their large stores of clint data to improve profitability and business growth.
Companies have been collecting billions of data on customers over the past decades. This includes information such as their buying habits and demographic information.
Sales intelligence tools can help you gather information, generate forecasts, and make decisions that are based on real, relevant data.
6. Improved customer acquisition
Machine learning is helping companies predict trends, prepare themselves for client inquiries, and get a better overall view of their products or services. Acquiring new clients is important for generating more revenue and companies are using machine learning algorithms on their CRM systems to find new ways to acquire customers.
A sales team is better equipped to anticipate industry trends, have a comprehensive understanding of products and services, and answer any client questions.
Businesses can improve their sales performance by using analytics with artificial intelligence to ensure that their sales reps are getting paid accurately.
The Benefits of AI and ML in Sales
Technology is all around us. From computers to cell phones to televisions, it’s hard to imagine what life would be like without it.
But it’s not just the physical device itself; it also includes the array of intelligence capabilities that it can perform in a matter of seconds. This is what sets technology apart and allows us to do so much more than we ever could before.
Artificial intelligence (or AI) and Machine Learning (or ML) are quickly becoming more and more popular, and are becoming staples in our everyday lives.
When we type something into Google, the search engine uses artificial intelligence and machine learning to autocomplete our query based on location, what other people are searching for, and past searches.
Companies like Amazon, Google, and Youtube all utilize artificial intelligence and machine learning to help recommend products, videos, and content that users may be interested in.
The future of sales with ML and AI
As AI continues to improve, we can expect to see more and more marketers using automated systems to reach their target market.
With the rise of artificial intelligence, the future of sales could involve all tedious, time-consuming tasks such as data entry being handled by machines, allowing sales teams to focus more on building new relationships.
As artificial intelligence and automation become more common, we humans are feeling threatened by our job security. Will sales jobs be replaced entirely by machines?
The personal touch of a human salesperson is unmatched.
While people prefer to have a human connection with someone before they buy something, machines can automate the more mundane tasks like entering data. This allows your sales team to spend more time doing what they are best at – selling.
Conclusion
Overall, machine learning in sales can be a huge asset. By helping to prioritize leads and understand customer behavior, it can make the entire process far more efficient and effective. In today’s competitive market, any edge that companies can get is important, and machine learning is certainly one of the most promising new tools out there.
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