Here’s how AI can revamp the sales and marketing sector

By Nikolas Kairinos

Artificial intelligence in Sales and marketing

Technological advancements offer businesses a great opportunity to reflect on what’s working well within their day-to-day operations, identify what needs improvement, and consider how new technologies can make them work smarter, not necessarily harder. One of the most influential technologies of our time, which is being eagerly embraced by business leaders across a host of industries, is artificial intelligence (AI).

With the ability to synthesise huge volumes of data and identify trends, AI is naturally positioned to support the Sales and Marketing (SaM) needs of businesses large and small. According to recent research, 40% of SaM 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 targets.

As someone who works closely with businesses and organisations to develop and implement AI toolsets, however, I’m well aware of the misapprehensions about this technology and the general lack of awareness that still exists about its practical capabilities.

For this reason, Fountech recently released a whitepaper offering guidance to those who are not well-versed in AI on how to embrace these solutions to ensure they are meeting their SaM targets. Below I outline some of the key considerations that businesses should take into account.

Helping teams create effective marketing campaigns
The essence of an effective marketing campaign is having a good understanding of your end-user. That’s why data has never been more valuable; through data, businesses can gauge consumer needs, and monitor how their demands change over time.

AI is starting to play an ever-growing role in creating customer profiles that can drive effective campaign strategies: it streamlines the process of building up a comprehensive profile by assessing huge swathes of customer data at granular levels, uncovering hidden patterns in their behaviour and thereafter churning out quality insights. In turn, this allows businesses to target the right customers, in the right way and at the right time.

Rather than talking in abstract terms, let’s consider a simple case study. Say a restaurant chain wants to attract more customers, but in order to do so it needs to know people’s eating habits — for instance, what day they are most likely to eat out, and even how the weather affects their preferences. The restaurant e-mails a digital voucher to its database, offering people a discount via a smartphone app, but one restriction applies — restaurant-goers can only take up the promotion on Tuesday evening over the coming two months.

AI is then called upon to perform an analysis of the behaviour of those users who took advantage of the promotion, and those who didn’t. It assesses a whole host of different data points, including participant’s proximity to the closest outlet, the weather on days the uptake was strongest, and even what events were taking place on the same evening.

It might reveal that people eat out more when it’s rainy outside, or that Tuesday isn’t a popular day because it coincides with TV coverage of football league events. To entice more customers, the restaurant can then use this insight to create more effective SaM campaigns.

Helping teams sell better
On the sales side, AI has also been a saving grace for many teams. Thanks to the unparalleled ability of AI-fueled solutions to scan through data stores, sales reps no longer have to spend endless hours trawling through prospective customer profiles only to be disappointed when the leads don’t convert to a sale.

So, what exactly can AI do? By creating buyer profiles, AI can handpick the right candidates for businesses to offer their products and services to; in essence, it takes over most of the grunt work and ensures that businesses are pitching to the people most likely to engage in a sale.

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 they only contact interested individuals and those that would be a good match for their own needs.

Such tools can even suggest lead prioritisation 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.

The benefits on offer from AI are endless, and this is evident when we consider how AI is being used as a tool to support the wider SaM efforts of different companies and organisations. It is an accessible and intuitive tool that can make you work smarter, not harder.

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