Machine learning may be a buzzword now, but what could it actually mean for business and sales down the line? Will salespeople be replaced by Rosie from “The Jetsons,” or the more frightening HAL?
Doubtful. But the ability to automate sales tasks could mean big changes on the horizon. These changes are all about how we leverage the new technology. With the right high-quality data, machine learning could transform how business is done.
We accept that data is the key to designing successful, personalized engagements with our customers. SAP recently commissioned a research report by Aberdeen, which discusses the importance of a “data-driven understanding” of our customers on a granular level. Many of us have already spent time and set up systems to collect and track customer data that we know will be useful. And with machine learning, we may finally be able to easily and effectively use that information we’ve collected in ways humans alone cannot.
Being able to sift through and analyze years of customer data to pinpoint trends and tailor your actions is something we’ve been working toward for a long time. Currently, this task tends to fall to sales personnel. But with machine learning, your advanced cloud CRM solution can learn over time to forecast and score deals with greater accuracy, freeing up sales team members to focus on building and nurturing relationships that add value to the business. Sales reps will more easily reach their numbers, and managers will see teams meeting and exceeding revenue goals. Machine learning offers the ability to simplify your organization by leveraging all the data you’ve collected.
Consider deal scoring, for example. Imagine if you could look at the data behind a prospect – the company size, the number of stakeholders, the types of solutions they’re looking at – and compare it to historical data you’ve collected from hundreds of past deals (both won and lost) to determine how likely it is to close. Machine learning could open the door to definitive deal scores, letting you more accurately predict how the deal will go, how long it will take, and how likely it is to close. You could tailor how you approach the deal to prime it for the win—or, if it’s not looking so hot, realign your team to focus them on deals more likely to close—all without the need to rely on the intuitive gut decisions.
Sales training is another example: What if you could pair new sales reps with a coach or assistant that could walk them through tasks one by one, reminding them to reach out to a client or nurture a customer based on timelines that have worked in the past? And what if you could do this without requiring the help of another salesperson, enabling your entire sales staff to focus on their goals?
With this technology, sales leaders will be able to provide accurate forecast predictions at a macro level, to understand trends segmented by sales organizations, sales reps, and sales stages. As more deals close, the system will learn and evolve to improve its future forecasts. Since the machine has no vested interests other than improving its own accuracy, it is largely independent of management pressures, removing sandbagging and gut feels from forecasts. Managers will have a clearer, more objective picture, quarter-to-quarter, of the health of the pipeline, and will be able to adjust in real time when needed.
Now, all this automation doesn’t happen automatically. It requires a lot of setup and thought into how you’re going to use it, and it absolutely requires accurate data. While machine learning may not be here quite yet, you can start preparing now so you’re ready when the time comes. The research provided by Aberdeen shows that best-in-class organizations “invest in data accuracy around their prospects’ and customers’ behavior.” Right now it’s about thinking big-picture: How can you transform your organization now to be ready for the changes when they happen, and to be able to react faster and have the systems in place?
Then it’s about changing how you think about what you’re doing – changing the business mindset. Business is no longer about the company; it hasn’t been for a while now. It’s about the customers, and helping each customer live better and easier. When we can be proactive, anticipating and addressing problems before they escalate so that customers never have to wait on hold, imagine how much better our relationships will be.
When we go down this line of thinking – automation, AI, and machine learning – it’s easy to jump back anxiously at the thought of robots taking over business. But worry not, sales folks. People – and human relationships – are not going away. In fact, if machines start crunching numbers on these scales for us, it will be more important than ever to engage personally with our customers and prospects. Sales reps will become relationship managers. Marketers will become industry experts, forecasting customer needs before they come up. Automating processes is a means to an end.
After all, there’s a personal side to selling that no technology can ever replace.
For more ideas on how your company can transform, read the full Aberdeen white paper, “Marketing/Sales Alignment 2016: Who is Agile Enough to Win?”
Learn how SAP Hybris can help you streamline and automate your sales force now.