Artificial intelligence has already crept into our businesses with voice assistants and chatbots, but it is also so much more than that. Look beyond the hype and learn about AI in sales through three use cases that are not less important for sales leaders.
It is the first of two blogs presenting the opportunities AI can bring to sales, this time from a management perspective.
As much as we are living in an age of digital transformation, according to current knowledge, robots will not replace sales reps any time soon. It means your task of managing humans remains. However, it is true that AI is finding its way in assisting the workers. The best thing about it is that you can be among the first to adopt it as a management tool: Adobe found that only 15% of enterprises are using it currently, but 31% plan to introduce it in the coming year.
1. Empowering and Developing the Team
A well-functioning sales team is vital for the business operation and, as a leader, it’s your task to provide advice and direction to your reps. From the onboarding of new colleagues to the motivation of old ones, you should welcome AI as a useful companion.
The first thing you want to make sure of is that you have all the tools to provide data. Moreover, since the intelligence making sense of a mess is yet to be discovered, data needs to be as clean and as consistent as possible.
You shouldn’t rely on the reps administering the contacts and logging the meetings. Artificial intelligence can dig their email correspondence for new leads. It can keep a log of the calls. It can be integrated into a mobile business app and used by field teams so you can see the data flowing in from all directions, to a central place. By motivating the reps to answer some simple question, AI can even assemble a todo-list based on the logs of the pipeline and schedule (follow-up) meetings with clients.
Then, further down the pipeline, AI will give the team a sense of accomplishment while setting the reps free of the tasks that everyone hates. It doubles for all of your team members as a personal artificial assistant and empowers them to focus on personal selling. AI gives the data (ideally from the CRM) to begin the conversation, finds highly relevant content (see sales enablement) that fits the situation of the client, based on industry, deal size, stage, and other factors. With the more tailored pitches, sales reps can win the well-prepared and demanding customer who expects the agent to know them.
2. Evaluating Performance
Effectiveness is always crucial for sales leaders as they need to meet the quota of the current quarter or business year. However, that’s when AI comes into the picture and can add value. From the data collected by the reps and their apps, the new intelligence can extract a meaningful analysis of performance.
You might have learned to look out for performance peaks or red flags in particular data sets: imagine that a machine not only learns that from you and delivers the actionable items to your fingertips, but also suggests new measurements of actions that can be translated to business performance.
How is it possible? AI is never in a time constraint to check the relations between all elements of the formula. Does the length of the meeting have an impact on deal success? How many times does an agent have to follow up? What is the ideal skill set for a winning team? With some settings of your preferences, you can find the answers to these questions in the automated report.
3. Forecasting Opportunities
This one is huge: the team of you and the AI will be winning every time you correctly recognize a business opportunity. So all the performance analysis serves one purpose: to improve the processes so that the business can profit from it.
You do that by trying to improve the accuracy of forecasting and predicting future events and translate it into figures to depict the earnings. By learning what actions and behaviors lead to sales, managers can act adequately on the opportunities, e.g., by setting the right priorities.
The artificial element of a corporate application can tell by the analysis of previously successful activities what the future actions should be. CRM’s powered up with AI, for example, can build new pipelines with priority rankings, out of the previous interactions with contacts. Also, the analysis of the deal sizes and contributing factors allow the AI to predict what the reps can bring in in a selected period. Now how is that for support of business planning?
In the next part, we will present you five up and coming AI apps that you can use for sales.
