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A sales team is only as good as the data it works with. However, HubSpot identified that B2B data decays at a rate of 22.5% annually, so sales teams must ensure the data they hold is always kept up-to-date and fit for business purpose, by cleaning and enriching stale data, filling in missing information and updating out-of-date records. Through the use of the latest AI technology, sales teams can work securely in the knowledge that the data they work with is of the best possible quality.
We will soon see AI’s natural language processing capability unlock the power of human speech, allowing chatbots to develop more advanced, human characteristics and interact with customers using natural, conversational language. This will have several practical applications for a sales team. For example, a chatbot could perform basic tasks, such as booking appointments or demos. They can also be used to reduce admin time by directly updating CRM records through a simple notepad style interface, enabling sales teams to update data in real time whilst on the move.
In 2019, AI will increasingly be used by businesses to analyse customer data, identify long-term trends and determine patterns of customer behaviour, with a view to anticipating what they will do next. This will enable businesses to create predictive experiences for their customers. Sales teams can use them to pitch to prospects at the times that they’re most likely to buy - if the prospect has recently switched jobs, for instance, or if the company they work for has relocated. If deployed correctly, AI can have a big impact on a sales team’s lead generation and revenue growth.
The cumulative effect of applying AI solutions to businesses is in freeing up time for human workers.
A good example of this effect is the traditional sales rep; a recent study of how sales reps spend their working day revealed that nearly 22% of their time is engaged in researching and prospecting for leads, which if managed by AI, creates a sizable chunk of time that the sales rep can then use to interact with clients and close more deals. Essentially, AI takes up the slack, allowing salespeople to get on with doing what they do best - selling!
One challenge that every salesperson will encounter at some point in their career is knowing what discount, if any, to give to a client. In the past, such decisions were often made by the salesperson following standard practice, or incomplete information, or simply their gut instinct. Today, the challenge of price optimisation can be solved by AI, augmenting the function of a sales team by providing it with accurate analytics that aids the process of closing deals and growing revenue.
Before the growth of AI, sales forecasting was initiated by teams of business analysts, and despite the analysts’ best efforts, the results were often incorrect and incomplete, subject to the vagaries of human error. One of the benefits of AI for any business lies in its ability to analyse vast quantities of data, at a much faster rate than any human can. AI algorithms are now able to predict, with a startling degree of accuracy, next quarter’s revenue. This information empowers sales managers to make better decisions, such as knowing exactly where in the business to allocate more manpower and resources.
A salesperson working with a pipeline of qualified prospects has to make decisions on a daily (sometimes hourly) basis on where to focus their time and energy. For salespeople who rise or fall on closing deals and hitting their quota, time management is a critical part of their daily routine. AI can compile all the historical information about a prospect and list them according to the probability of the deal being closed successfully. By maintaining an accurate lead scoring system, AI points the salesperson in the right direction, towards the most favourable deals and prospects.
Every salesperson knows that the fastest and most economical way to achieve revenue growth is to sell more to their existing clients. Working out which customers are likely to buy more was never an exact science - until now. AI can scan a customer’s buying history, social media posts, and any changes in circumstance. The benefits of using AI in upselling and cross-selling opportunities are increased revenue for the sales team and a drop in associated marketing costs.
Every month, sales team leaders are tasked with assessing the revenue pipelines of each of their salespeople, with a view to highlighting which deals are likely to be successful and which deals are likely to fall through. AI enhances this process - now, sales managers can use dashboards to see on a visual level which salespeople stand the best chance of hitting their quota. The insights gained from this data allows managers to focus attention and resources on their key salespeople and the deals that are most likely to be closed.
When AI first started to be used by businesses, it was primarily confined to automating manual tasks such as data entry, customer support and lead prospecting. Through its ability to analyse big data, and integrate into existing software and platforms, over the next 12 months AI will be able to evaluate results, predict future trends and suggest profitable courses of action. Using AI, sales managers will be able to identify accounts that have the greatest chance of success at a faster pace than normal, meaning that they can quickly refocus energy and resources to those parts of the business. Sales teams that regularly use AI as part of their decision making will acquire a competitive edge over their rivals.
Conclusion
AI is not static technology; it’s changing and evolving all the time. The organisations that embrace the full possibilities of the technology will see the tremendous benefits it can offer in visualising, identifying and engaging their next greatest opportunity, with the ultimate goal of maximising revenue generation.
