5 Best Uses for Artificial Intelligence in B2B Sales in 2022

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Seventy-five percent of salespeople believe that they could not do their jobs as effectively without current technologies, according to our latest research. Technology is essential in a world that relies on it to evolve and enhance the way sales teams connect and follow up with leads. Now artificial intelligence (AI) has become a key piece of the puzzle.

AI empowers sales and marketing teams to do more and do better, transforming any personalized marketing initiative into an intelligent and highly effective strategy that delivers results. Let’s look at five AI-assisted technologies that are poised to bring the most significant results to B2B sales in 2022.

Spend more time on impactful tasks with faster conversion

With a deluge of data coming in – and more being generated every year – no one can keep up. The naked eye cannot detect subtle purchasing behavior patterns among customers, leaving gaps that could cause them to miss out on crucial sales opportunities. That’s where AI comes in. AI can help sales and marketing leaders understand buyer behavior and readiness, especially when paired with insights about which prospects have taken actions such as answering a cold call or responding to an email in the past 60 days.

AI can create accurate and reliable projections based on all client interactions and historical sales results, such as which mediums are more likely to result in conversions. Over time, they can build automated forecast models to analyze future demand in real-time. In doing so, manual calculations will no longer be necessary, giving sales reps more time to spend on high-priority tasks that will have a more substantial business impact.

Use AI to improve lead nurturing

The great thing about automation is that it builds on other tools, strategies and technologies. This is especially evident with lead nurturing – when real-time data is used, sales professionals can customize their communications in the most relevant way possible. Whether information is gathered from email open or click-through rates or from social media engagement or another source entirely, automation can assist teams in collecting pertinent information across all touchpoints.

With easy-to-digest reports (including handy visual charts), sales leaders can improve nurturing efforts and engage more effectively with target audiences. From there, sales teams will be better equipped to provide a selection of content that will be most appealing to prospects.

Make lead scoring models more efficient with AI

Lead scoring is another critical process for sales teams, enabling them to identify the most high-value, high-priority individuals among a selected group of qualified leads. This may differ across businesses, but many rely on data from past leads to create a customized value system that assigns “points” to new prospects. Those points may be based on demographics, engagement history, company information, and communication preference, informing which prospects are likely to be converted.

But like most processes, lead scoring takes time. With AI, lead scoring models become more efficient; sales teams can quickly compile and analyze past customer data to create algorithms that rank successful conversion opportunities. Data analytics improves the process even further by enabling attribution reports that pull all relevant interactions from previous customers to see which channels and which types of content are driving the best results.

Deploy AI for a more personalized approach

Anyone can deploy a broad approach, but a more specific, personalized marketing strategy will likely yield better results. It has become quite common in the digital on-demand age, a time when businesses and consumers alike can move from one seller to the next with the click of a button. AI-assisted technology strengthens personalized marketing with greater intelligence. A wide range of data – such as location, demographics, engagement behavior, and past purchase history – are factored in to help businesses pinpoint the most relevant content and product offers for each individual prospect.

The end result should not be overlooked. According to a report by Boston Consulting Group, organizations that master personalization can increase their growth rates by as much as 10%, improving marketing efficiency, boosting digital sales and building stronger relationships with their customers.

Turn to AI for better SEO optimization

Last but not least is SEO optimization, another time-consuming process that, if performed manually, would be nearly impossible to complete. There is simply too much digital content for human beings to process by hand. AI and machine learning (ML) can do all of the heavy lifting on their own and automatically perform search volume analysis to identify patterns in the data. This makes it possible to build intelligent algorithms based on those metrics and ultimately create SEO-optimized content that succeeds every time.

Ultimately, AI is an incredibly valuable technology that is already helping sales do more, work faster and deliver better results. As more people in sales and marketing catch on to its potential, they will be able to take full advantage of the technology to more accurately and intelligently target prospects and create more robust algorithms. AI also empowers sales teams to focus on higher-value objectives instead of the monotonous and time-consuming tasks they performed manually before adopting the technology.

Monica Sullivan
Monica is a marketing leader with extensive experience building and leading teams and creating capabilities to achieve objectives in high-growth, dynamic organizations. Before joining Demand Science, she served as SVP B2B Marketing at Gannett, with responsibility for brand and acquisition marketing. Previously, she held senior positions such as Vice President, Acquisition Marketing at Constant Contact, President at d50 Media, Vice President, Corporate Advertising at Caesars Entertainment, and Vice President/Director at Digitas.

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