Artificial intelligence: 10 Statistics About AI in Marketing and Sales
Who will win in the impending war between artificial intelligence (AI) and humanity? No one really knows, but if the battles are waged in the arena of B2B sales, then I have a hunch that the robots might have the upper hand. In fact, various real use cases already exist for artificial intelligence in sales.
As the term “artificial intelligence” is thrown around more and more, what is actually AI is becoming progressively further undefined in the eyes of the public. Terms such as “machine learning”, and “deep learning” often get confused with the overall AI definition. Furthermore, the number of startups bundling “artificial intelligence” unnecessarily into their value proposition to obtain more funding is consistently on the rise.
Nevertheless, there are a number of concrete examples of how artificial intelligence is rising to prominence within the sales context. Do not worry salespeople, these facts may not point to your immediate replacement by a robot but it might mean that some adjustments will have to be made within your department to not fall behind in the race towards singularity.
High performing sales teams are 2.8x more likely to be very proficient in predictive intelligence.
Predictive analytics means using historical data, machine learning, and artificial intelligence to predict what will happen in the future. For example, within a marketing and sales context, it might mean mapping customer behaviour. To supplement this high-performance correlation with predictive intelligence, Deloitte found that 83% of the most aggressive adopters of AI have already achieved moderate or substantial benefits.
It is predicted that by 2020, 30% of all B2B companies will be using AI to improve at least one of their main sales processes.
This trend of replacing or supplementing sales processes with artificial intelligence is here to stay. In fact, Forrester indicated that 46% of companies say that marketing and sales are the areas in which they are investing the most in terms of new AI systems.
The adoption of AI by sales teams is expected to grow by 139% in the coming three years; this makes it the top growth area for sales.
Salesforce also predicts in lead-to-cash process automation (115%) within the coming three years.
Currently, 40% of sales tasks could already be automated, and McKinsey predicts that by 2020, 85% of them will be automated.
A study by Sales for Life found that the average SDR performs 95 activities a day, and only one-third of the day actually talking to prospects. Notably, InsideSales.com found that 63.4% of the reps’ activities are non-revenue-generating. The B2B Lead also found that reps waste 50% of their time on unproductive prospecting and 32% of their time is spent searching for missing data and manually entering it into the CRM according to IKO system. If all these statistics are taken into account, it becomes clear that there is a large amount of inefficiency where automation could potentially save both time and money.
A study by Harvard Business Review revealed that companies using AI for sales increased their leads by over 50% as well as leading to cost reductions of almost 40-60% (Salesforce).
This study also found that AI reduced call time by 60-70%. These statistics show clear benefits for companies willing and able to implement AI within their sales departments.
It is forecasted that one million B2B salespeople will lose their jobs to self-service e-commerce by 2020.
Self-service e-commerce is more typically focused on B2C but the impacts of artificial intelligence are expected to affect the B2B salespeople that are still involved in the running of an e-commerce website.
The percentage of B2B marketers considering AI valuable for their sales or strategy is on the rise and already at 64%.
If one looks at businesses overall, 83% mention AI as a priority for their strategy today. Due to this growing belief, and alongside the increased focus of inputting AI into business processes, whether in sales, marketing or any other department, it’s apparent that sales reps must begin to adapt their skills to these advancements. This is highlighted by the fact that 36% of executives believe that the primary goal for AI is to enable workers to be more creative in their jobs by automating menial tasks.
Automating activities such as email campaigns and sales follow-ups has led to a 14.5% increase in sales productivity according to Salesforce.
This is an easy one people, if you like sales, you like sales productivity.
75% of buyers expect companies to predict their needs and make relevant suggestions before contact.
Triple-digit growth is expected in artificial intelligence areas which will enhance these types of capabilities. Namely, Salesforce expects 118% growth in predictive intelligence over the course of the next three years.
Salesforce found that 56% of buyers look actively to purchase from companies that they perceive as most innovative.
Yes, we did say that we don’t applaud companies throwing AI into their company bio only to generate more investment or leads. Nevertheless, implementing AI in real use-cases within your company that are visible in the sales interactions with your leads can lead to a significant uptick in growth.
Despite these statistics showing the fast adoption of AI in sales, there is nonetheless a gap to fill. Although MIT found that 85% of executives believe that AI will enable their companies to achieve a competitive advantage, only 39% have an AI strategy and only 20% have AI already incorporated into their business in some way. This shows that there is still potential to be an early mover in terms of adopting AI into your sales team to win out the competition.
If all these statistics leave you a little bit overwhelmed, do not fear, there are various use-cases for artificial intelligence worth checking out in the following article.