Across all industries, business leaders are waking up to the massive potential of artificial intelligence (AI) in powering decision-making processes and streamlining complicated or laborious tasks. The sales and marketing sector (SaM) is certainly no different – for years, professionals in this space have been searching for ways to more effectively target their customers and close quality leads. Thanks to AI, there are now a plethora of toolsets readily available to help them do just that.
This might explain why in the last 12 months, there has been a significant uptake in the number of SaM professionals looking to this technology to help boost sales, increase customers and ultimately promote their business. According to research, 40% of marketing and sales teams today recognise the importance of AI, and in particular machine learning (a subset of AI) in ensuring they are able to pursue and accomplish their set targets.
AI excites people, but when it comes to actual adoption and integration, businesses can be dissuaded. There is a general perception that it is either too complicated, too expensive or simply not relevant. In reality, I believe that the only significant barrier preventing companies from embracing AI is a lack of knowledge and awareness about its practical application. While AI adoption is becoming increasingly widespread, the term conjures only a vague understanding for those who are not well-versed in this technology. That’s why at Fountech, we recently released a whitepaper that not only explains how AI is revolutionising the SaM sector, but also offers practical guidance for business leaders on the toolsets currently available on the market, and how they can be harnessed to achieve their targets.
To offer some insight into the rapidly changing SaM landscape, below are some of the main ways that AI can help support sales and marketing teams.
It’s all in the power of automation
All businesses in the private sector understand the importance of SaM in promoting their products or services to potential customers. After all, the art of generating fresh leads and effectively selling to them is the lifeblood of any company. So, how can AI help companies sell better?
At a fundamental level, AI can help SaM teams overcome some of the common challenges they face. Perhaps the most important of these is the need to maintain a comprehensive view of market trends so that they can understand their current and potential customers’ various needs and goals. Given the amount of data that is now available to businesses, AI can be leveraged to quickly and effectively process huge reams of quantitative and qualitative data.
Scouring spreadsheets, buying data and relying on traditional sales techniques such as cold calling, for instance, are incredibly time-consuming and often deliver limited results. This is where AI comes in: it streamlines the process of building a profile by assessing huge swathes of customer data at granular levels, uncovering hidden patterns in their behaviour, and thereafter churning out quality insights. What’s more, it does this at speeds that can’t be matched by humans.
Driving effective marketing campaigns
Let’s now consider how this ability might be leveraged by SaM professionals in the context of their everyday responsibilities.
By compiling relevant information about a customer – from their online behaviour to previous interactions they might have had with the business – AI toolsets are able to generate a comprehensive digital profile of individuals. This means that businesses can cater to them much more effectively through hyper-personalised content that is targeted.
To offer a simple example, a restaurant chain might send out a promotion to its database of customers via e-mail, offering them a discount through a smartphone app on a certain day of the week.
Once distributed, AI-powered toolsets would then be able to assess different data points – the rate of uptake, geographic issues and even weather patterns – to ultimately suggest people’s sentiments towards such promotions, the motivations behind them taking up (or not taking up) the offer, and the factors that make this given day a popular or unpopular time to eat at the restaurant.
Based on this in-depth analysis of the campaign, the business can then alter their marketing strategy to make it even more effective the next time around. For instance, if the data revealed that Tuesdays weren’t a popular day to eat out at the restaurant because there were often big sporting events on that night, the restaurant chain might implement a discount for takeaway deliveries on that day in order to drive more sales.
This leads nicely onto my next point: another field in which AI excels in is finding high-quality sales leads that reflect the particular needs of a business. This has the potential to save professionals countless hours otherwise spent on trawling through digital profiles and searching for prospective candidates that may or may not ultimately result in a successful sale or a close.
Indeed, the McKinsey Global Institute found that 40% of tasks performed as part of a traditional sales function can be automated, and this number is projected to rise to 50% with further advancements in AI technologies.
The role of machine learning is key here, giving these AI tools the ability to learn from the outcome of past actions and continuously improve in order to produce only the most hyper-relevant leads. Put simply, the more that sales professionals engage with AI solutions in accepting, declining and forwarding the leads it provides, the better it will be able to learn what the business’ ideal client looks like, meaning that it can refine its search.
It goes without saying that further advances can and will be made in this field, and the above only offers a small glimpse of the potential on offer. But most importantly, I hope I have emphasised how easily AI-driven solutions can be integrated into everyday business operations: entering the brave new world of AI is much smoother and accessible than you might think.