At some level, sales controls the demand for your offering. The more you sell, the more demand there is. For the longest time, especially in the B2B sector, the whole process was incredibly manual. Any meaningful increase in results could only be gained by hiring more people.
Gradually, automated tools entered the B2B space and offered raw processing power and efficiency. Starting with organizing all your contacts and third-party relationships in a CRM to recording the movement along your conversion funnel and predicting sales outcomes.
Sales forecasting is one of the most important activities used to calibrate business growth. But modern sales forecasting methods such as weighted pipeline forecasting, which multiplies the likelihood of every deal in the pipeline closing by revenue, tend to be inaccurate.
Most sales activities, calculations, and predictions can be greatly enhanced with the use of artificial intelligence and machine learning, which run on models that can process hundreds of inputs and millions of data points in real time. Here are just a few ideas for how this kind of computing power can be applicable to predicting sales and improving your sales process overall.
Although frequently overlooked, one of the best ways to improve your sales numbers is cutting your churn — the percentage of customers leaving who no longer use your service.
A lot of businesses are already adopting AI-powered tools such as chatbots to ensure every customer can access customer service (even if it’s just intelligent automation) and resolve their issue in time, regardless of the size of your customer base.
According to industry surveys, only one in 26 unhappy customers actually makes a complaint. The others are highly susceptible to churn and are likely to leave unless you offer them an effortless way to get in touch or you proactively reach out to them.
The best source of revenue, without doubt, is your existing customer base. In fact, upselling an existing customer is four times cheaper than acquiring a new one. To do that, however, you need to be able to closely track every customer journey.
AI sales tools can help you understand the market dynamics and provide your sales team with customer insights, preferences, and pain points that can be used to initiate various campaigns, from suggestions for complementary product integrations to reiterating your unique value against competitors.
Increasing Close Rates
Another critical aspect in predicting sales is evaluating the percentage of opportunities you win. As B2B sales cycles can stretch for months and involve multiple stakeholders, forecasting closing rates remains largely subjective, not incorporating all the auxiliary data available to you. As a result, just 47% of forecasted sales actually close.
Leveraging the power of AI, you can identify decision-makers and internal champions who might not stand out in the organizational chart but hold a lot of influence over the probability of the deal closing. AI tools can also help you facilitate the right conversations and shorten the sales cycle.
Providing Accurate Lead Scoring
One of the most difficult and even mysterious aspects of predicting sales in the digital age is determining buyer intent. Making decisions based on misleading buying signals or incorrect information is costly, to the point that many organizations don’t believe lead scoring adds value anymore.
In fact, lead scoring and successfully identifying strong buyer intent can significantly boost your conversion rates. When your BDRs are able to single out those who are very likely to buy, the whole sales process gets much easier. You just need a powerful AI sales tool to make the correct assessment.
Lift AI is one of the most impactful solutions in the B2B market today. This anonymous buyer intent platform leverages a proprietary machine-learning model that works with more than one billion data points and makes real-time decisions based on over 14 million live sales engagements — all to determine the buyer intent of every single visitor on your website. Lift AI works even when your website visitors are completely anonymous and previously unknown to your marketing systems (e.g. CRM). Recent studies show that up to 98% of your traffic can be anonymous.
The ability to determine buyer intent is a key factor to predicting sales. When your BDRs spend most of their time talking to people with the highest buyer intent, they tend to sell more, considerably more.
The way Lift AI integrates into your sales workflow is by seamlessly improving your existing enterprise chat platform (e.g. LivePerson or Drift). It assigns scores to every visitor and places them into one of three cohorts (high, medium, low) based on buyer intent with 85% accuracy.
Visitors with high buyer intent (about 9% of the overall traffic) get connected directly to your BDRs through chat. Medium and low-scoring visitors in turn are greeted with a nurturing bot or a self-help guide to assist them in moving to the next step of the conversion funnel.
Lift AI customers have often reported up to a tenfold increase in chat conversions after using Lift AI for 90 days. All due to your BDRs easily connecting with the best visitors first.
Accurate lead scoring with anonymous buyer intent would make predicting sales and planning your overall sales strategy much easier. You can see how AI and machine-learning tools such as Lift AI are able to boost conversions without any extra human resource expenditures involved and give you more control over your B2B sales cycle.