How will AI disrupt the sales and marketing sector? [Q&A]
The Sales and Marketing (SaM) environment has undergone a fundamental shift over the past decade, driven largely by the proliferation of accessible artificial intelligence (AI) toolsets. According to recent research, 40 percent of marketing and sales teams today recognize the importance of AI, and in particular machine learning (a subset of AI) in ensuring they are able to pursue and accomplish their growth goals.
But what makes this technology so powerful? The answer lies in automation. Namely, AI has the ability to automate tedious, complicated, and time-consuming tasks (which would otherwise be left to SaM professionals), leaving professionals to focus on more value-adding activities such as managing projects and making high-level strategic decisions.
It's no surprise that businesses across the sector now implement AI solutions to undertake a whole host of different jobs, from compiling customer profiles to ensuring the effectiveness of marketing and sales campaigns. But there are many misapprehensions about this technology and the general lack of awareness that still exists about its practical capabilities.
Fountech recently released a whitepaper offering guidance to those SaM professionals who are not well-versed in AI, explaining how existing toolsets can be readily embraced to transform existing business operations. We spoke to Nikolas Kairinos, CEO and co-founder of Prospex and Fountech to explore the use of AI in sales and marketing.
BN: How can AI be used to create effective marketing campaigns?
NK: Data is now more useful than ever, and can be utilized to drive effective campaign strategies which not only target the right customers, but also provide an appropriate way to engage with them. Indeed, the hallmark of an effective marketing campaign centres on building up a profile of the end-user and personalizing the messaging towards that particular individual.
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 behavior, and thereafter churning out quality insights.
BN: How might this work in practice?
NK: A simple case-study might shed some light on how businesses might use AI to drive an effective marketing campaign. Let's say, for instance, that a digital voucher is e-mailed to a restaurant’s database offering people a discount via a smartphone app. To ensure that the restaurant can keep up with demand, the promotion is limited only to Tuesday evenings over the coming two months.
To test how successful the campaign was, and to offer an understanding of how the restaurant might entice more customers, AI is called upon to perform an analysis of the behavior of those users who took advantage of the promotion, and those who didn't.
This isn't to say that, without AI, businesses can't conduct a post-campaign assessment. However, the degree to which they were able to gain insights is limited primarily to survey responses voluntarily offered by the recipients, and manually tracking the uptake of the promotion. With AI, the restaurant can delve much deeper – not only to assess whether Tuesday is a popular day to visit the restaurant, but in also understanding what can be done to encourage more people to visit on that given day.
Confirmatory data might suggest the motivations behind people's choices to take up the offer or not, their sentiments towards these kinds of promotions, any geographical issues involved such as customers being too far away from participating restaurants, and even weather patterns (it might be the case that people tend not to go out to eat as much on hot days).
This is hardly a complete list of data that can be gathered, but it does offer an indication of the number of variables that can be examined. Upon analyzing the results, the business might learn that Tuesdays aren't popular for restaurant-goers due to TV coverage of football league events taking place on those evenings. In response, it would be wise to offer discounted deliveries to coincide with these events to help drive sales.
BN: How can AI help sales reps?
NK: In days gone by, sales reps have spent hours trawling through social media platforms and scanning company pages to handpick the right candidates to offer their products and services to. By creating buyer profiles, AI can make this process infinitely faster and carry out most of the grunt work typically done by humans -- ensuring that businesses are pitching, engaging with, and marketing to the right people.
AI can gather the data, analyse it at speed, and pick out promising leads that are likely to change from prospects to valued clients. Lead generation is therefore one of the most promising applications of AI solutions for businesses; toolsets like Prospex can deliver important customer insights to sales reps, ensuring that they only contact interested individuals and those that would be a good match for their own needs.
Such tools can even suggest lead prioritization to indicate where sales professionals should be diverting their attention. By using Weighted Probability and various machine learning methods, AI-powered tools are able to assign a score to leads that indicate their buying probability. These functions can also be used to predict which existing customers have more chance of buying a better product (up-selling), or a new product (cross-selling), helping teams more accurately target leads that have the best chances of closing.
How it does this is intuitive -- the AI uses historical data of customer behaviour and compares it with the data of those with a similar profile who have purchased better or new products.
BN: Is this just the start of a major shift in the way sales works?
NK: The above examples are just a few of the many ways that this technology can, and should, be leveraged by businesses in the SaM sector to improve their output and reduce the burden on their employees. The most exciting thing is that as AI toolsets are developed and improved, there are growing numbers of solutions available to experiment with in order to gain a competitive advantage.
Nick Kairinos is the CEO and co-founder of both Prospex and Fountech. Prospex is a sales and marketing solution that delivers AI-powered leads. Developed in partnership with LOMi and Fountech, a leading AI development company, Prospex applies sophisticated AI technology to provide qualified, hyper-personalized and cost-effective leads for small businesses through to large corporates.