Data is the currency of choice for companies looking to cash in on customers. In a world of start-ups and seed funds, being cash poor matters less when you’re data rich. Data is the basis for the effective use of machine-learning, AI, and one of this year’s hottest trends in customer relationship management—predictive analytics.
From pricing to forecasting to lead management, predictive analytics uses technologies that leverage customer data to be able to make smarter predictions about business outcomes.
Yet, knowing how to effectively translate data into actionable insights is challenging for companies with little to no experience in data analysis.
AI is making a big impact on how sales teams function. It won’t replace your sales manager, but the use of artificial intelligence in sales can automate some of the menial tasks involved in successfully closing a deal. Eliminate data entry? Check. Source leads? Check. Spend less time crafting an email? Check.
The problem is that small businesses struggle with incorporating AI into their sales processes on a tight budget. Knowing which software to invest in—and what gives the biggest ROI—is daunting for small businesses that don’t know enough about AI to comfortably navigate the landscape.
The easiest way to get started is by using sales tools with built-in AI capabilities. Many CRMs and sales software tools have incorporated AI and machine learning into their offerings, allowing for an accessible introduction for small businesses looking to use artificial intelligence in their sales processes.
And it’s wise to get started sooner rather than later.
Talk of an AI-automated workforce is making people nervous. With predictions nearing 50 percent of the entire US workforce being replaced by some form of automation, AI is a glaring threat for employees unsure of the capability of this burgeoning technology to replace them.
Last year, HubSpot published an article outlining the jobs that were most and least likely to be replaced by AI. Based on a landmark study out of Oxford University, it analyzed the likelihood of AI replacing jobs depending on their level of repetitiveness and the amount of specialized training and social intelligence they required.
More than a third of marketers don’t know how to use data for decision-making.
Between not knowing which data is useful and how to interpret the data that is, marketers are left with a mountain of information they’re not quite sure how to climb.
The good news is that you’re already collecting data you can leverage to make analytical decisions about your business and its sales and marketing strategies.
Selling is a lot easier when you know the ins and outs of the product you’re trying to sell. Imagine convincing someone to buy a house without knowing the square footage, location, or year it was built. Pretty impossible, right?
Sales enablement takes that same logic and applies it to B2B sales. It aims to predict buyer expectations so that the sales team is better equipped with the information they need to help them sell.
According to Gartner, a sales enablement program provides teams with the materials and processes that support a knowledge-based approach to sales. This can range from content, to training and educational resources, to the use of technologies to help empower the sales force to close more deals.
But implementing a sales enablement program is only half the battle. The other half is being able to measure its effectiveness.