Sales forecasting is a critical component of any business strategy. Many sales teams find it difficult, if not impossible, to create consistent and accurate forecasting models.
How can you tell if you’re looking at a trend or an anomaly? Forecasting would be so much simpler if we could just read our buyers’ minds.
While it’s not exactly mind-reading, artificial intelligence (AI) offers a solution to your forecasting problems. Teams can develop more accurate sales forecasting with machine learning and AI tools.
It’s not always easy to adopt new technology, but staying on top of industry trends remains a proven tactic. Enhancing sales forecasting with machine learning can yield several measurable benefits:
Imagine how much faster and easier it would be to use artificial intelligence in sales forecasting. Like any tool, there are tips and tricks to make it even easier and more effective.
Sales teams rely on data for everything from building campaigns to setting follow-ups. The more comprehensive the data, the better the decision-making at every turn. Even the most talented human can only process a fraction of what AI can cover, leading to incomplete information and inaccurate conclusions.
Leveraging AI for data processing and analytics empowers your team by filling any gaps, working through test scenarios, and evaluating historical data across portfolios. Ultimately, AI can identify trends that a human can’t see.
Using AI for sales forecasting is faster and more efficient, which saves firms time and money. Sales teams can use their time more efficiently, like interacting with qualified leads to convert prospects into buyers.
Predictive analytics pairs algorithms with expansive data, both internal and external, to identify trends. Humans simply cannot process the volumes of data required to accomplish this feat. Using AI to process an immense amount of data and deliver reports reduces the error margin and provides a clearer picture to craft a more accurate model.
Lead scoring is one of the most beneficial aspects of sales forecasting using machine learning. Sales teams rely on AI to predict which leads are most likely to convert based on longitudinal data and prospect behaviours at each stage of the sales pipeline.
Did You Know? Lead scoring can boost conversion rates by up to 20% while simultaneously reducing churn rates by up to 30%. By prioritising and targeting the most promising leads, businesses can optimise their sales strategies, leading to improved conversion outcomes and fostering longer-lasting relationships with clients.
Effective lead scoring relies on analysis of longitudinal and real-time data, far more than a human could process. Using AI, it’s possible to identify those prospects most likely to convert at the optimal time, so your sales team can use their time more effectively.
Have you ever had a simple question about a product? Maybe you go to the website to search for the answer only to come up empty. You might have given up and walked away without making the purchase.
What if a chatbot popped up on the screen, you typed in your question, and immediately got the answer?
AI makes it possible for teams to engage with their prospects when it matters most. Conversational artificial intelligence engages with leads even when you can’t. Providing information on your prospect’s timeline could be the difference between a conversion and a dropout.
Additionally, using AI chatbots means additional information about customer behaviours. The program tracks customer questions to provide useful analytics leading to better customer engagement and more efficient answers. Your team learns what customers want to know and allows them to communicate proactively.
Instead of bogging down employees with tedious weekly reports, let AI take over. Leveraging machine learning is faster and covers more ground, including real-time data. It’s far easier to connect every data source, like multiple social media platforms, and identify key patterns to guide your next campaign.
Further, analysing longitudinal data with real-time data is out of the scope of human ability, but artificial intelligence can do it, creating more accurate forecasting models.
64% of businesses look to AI for productivity boosts, mostly by streamlining daily processes. In essence, companies are increasingly recognising the transformative potential of AI to automate repetitive tasks and enhance operational efficiency.
Using AI to automate some of the mundane, time-consuming tasks alleviates stress on employees. It increases not only their productivity but also their job satisfaction.
As you make the leap to sales forecasting with machine learning, you need the right tools to succeed. Drawing everything together under one umbrella may seem impossible, but Forward offers a viable solution.
Using machine learning and artificial intelligence in sales forecasting isn’t the future of sales, it’s the present. To compete in today’s world, you need to leverage all possible tools to find an edge.
Boosting sales forecasting with machine learning and AI involves collaboration between teams and access to data. Leveraging AI allows teams to automate mundane tasks and devote more time to client interactions - with the right leads.
Forward supports sales teams by incorporating AI at every stage of the process. From gathering and organising data to real-time collaboration between teams, your team can function more efficiently and effectively.