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How to use Artificial Intelligence to boost sales

By Michael Brenner 10 January, 2019 0 Comments

Artificial intelligence is moving out of the realms of science fiction and futurist technologies. AI now has many practical applications that are used in the real world of business today.

AI software can be implemented in several areas of your business from customer service to sales and marketing. In this post, we’ll take a look at some of the ways that you can use AI to boost your sales figures and improve your company’s bottom line.

Personalize Customer Experiences

Personalization is certainly one of the biggest buzzwords in sales today but it’s not just a passing fad. The truth is, personalization works – customers have come to expect a personalized experience and so generic sales and marketing messages are becoming less effective.

Over 90% of consumers say they are more likely to shop with brands that recognize them and provide relevant offers. Over 80% are willing to provide their personal data in order to enable a more personalized customer experience.

AI is not necessary for personalization of course, but it can certainly help to deliver a more unique customer experience to each individual.

One example where AI works in this regard is the personal recommendation engines that are used on sites like Amazon and Netflix. These machine learning algorithms analyze data including browsing behavior, past customer interactions, previous purchases, and the purchases of other customers who share certain behaviors or characteristics. This information is used to automatically recommend products that are highly likely to be of interest to each user, rather than a more generic selection of items that are somewhat similar to items purchased in the past.

Automatically Score Leads and Refine Your Sales Funnel

Machines can not yet beat the sales skills of human beings. Where they do excel is in their ability to process vast quantities of data.

This means that AI software is a highly efficient tool for spotting trends and patterns in customer data. It can automatically score leads in a way that is more accurate and less subjective than manual scoring.

AI lead scoring enables sales teams to concentrate on their most valuable leads and return less-qualified leads to the marketing team for further nurturing through the sales funnel.

Using sales software that uses predictive analytics to score leads means that sales and marketing teams have more time to spend interacting with prospects and crafting effective marketing campaigns. Valuable staff resources no longer have to be spent on analyzing data and attempting to score leads and identify the best prospects manually.

Predict Cross-sells and Up-sells

Just as AI is effective at identifying those leads that are most likely to convert, it is also able to predict the cross-sells and up-sells that a sales team is most likely to be successful with for each individual lead.

Machine learning software can analyze data from previous interactions with a lead and previous sales with other customers to predict the products and services that will be most attractive to each lead.

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This eliminates the guesswork that sales teams have to do when it comes to cross-selling and reduces the risk of annoying existing customers with excessive cross-selling of products and services they’re not interested in.

There is a lot of money to be made in cross-sells and up-sells – you have a 60 – 70% chance of selling to an existing customer, compared to only a 5-20% chance for a new prospect. However, many companies don’t use the opportunity for cross-selling to its full advantage due to lack of understanding of customer needs. AI helps to fill this gap in knowledge, squeezing more sales out of each prospect.

Optimize Your Marketing Messages

How do you know that your website copy, emails, display ads, sponsored search listings, social media posts, and other marketing messages are effective? The truth is that you don’t know, at least until you can start collecting dating and carrying out some A/B tests in order to optimize your campaigns.

There are best practices to follow when it comes to writing sales copy and designing marketing communications of course. But these guidelines are generic and may or may not apply to your unique industry or audience.

How do you know if a picture of a male or female on your Facebook ad will result in more sales? You can make a good guess based on what you know about your audience, or you can carry out a split test with two different versions of your ad. Split A/B testing will confirm what you need to know but it takes significant time and effort. Figured out that the blonde girl picture performs better than the brunette? Great, but now it’s time to test some different headlines – you can see how this becomes a never-ending task.

Luckily for today’s marketers, there is another option – machine learning algorithms can be used to automatically make changes to your online marketing assets based on real-time interactions from each user. Over time your marketing messages will automatically optimize to the version that’s most likely to result in a sale.

And what’s more, this doesn’t necessarily mean one version is the best version for all users. AI software is intelligent enough to analyze all the data and optimize in real-time for different types of leads based on demographics, previous brand interactions, and any number of other factors. This type of personalized optimization is only possible when supported by AI-powered software.

Augment Your Customer Service and Sales Team with Chatbots

No matter how effective your marketing messages are, sometimes a lead will want to talk to a human being before making the final sales decision.

Or sometimes they may just want to feel like they’re talking with a human. In these cases, AI provides an effective substitute that is available 24/7 and is more efficient than a real human operator.

AI chatbots can be programmed to answer basic questions about products and services, provide customer support and service, make cross-sells and upsells, and direct queries to human employees in customer service or sales when necessary.

This reduces the load on human operators and enables website users to get answers to their questions at any time, even if your online chat service is only staffed during working hours.

An instant response to queries means that in many cases, barriers to conversion are eliminated, helping you to make sales at any time of the day or night.


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