One of the greatest things about digital marketing is that it is always at the forefront of the most recent online technologies. Machine learning is the most cutting-edge technology at the moment, and not just large companies have started to use it. Over 80% of online marketing agencies reported that their AI and machine-learning efforts had been deployed or increased since 2018, which is a long time ago.
Machine learning is set to become the next step in harnessing data to take marketing efforts to new heights. These are five ways that machine learning can improve any marketing plan.
1. Follow the Purchasing Journey of Individual Customers
Personalization is a key component in virtually all aspects of marketing. Although there is always speculation that personalization is old-hat, it often involves the simplest efforts such as including a person’s name in an email. Machine learning allows for much more.
Personalizing sales funnels is perhaps the greatest benefit of machine learning. Technology allows you to display relevant content to everyone, from website visitors to emails and anyone who sees your ads to anyone who fills out a form.
2. Get insight into the next products to promote
Artificial intelligence is a great tool for product marketing because it gives valuable information based on people’s activities about what they want to buy. This data is similar to the kind that can take hours, work, or a lot of luck to find manually. This technology provides real reasons to promote products and informs marketers about the best ways to do it. It can monitor chatbots and track ads and links.
3. Split Testing offers greater opportunities
Split-testing has been a cornerstone in digital marketing since its inception. It has been a slow, but effective way to determine what your audience wants.
Speed is key. Machine learning allows marketers to quickly launch split testing campaigns and then instantly understand the results. The adjustment phase is completely automated if it’s done correctly. Your AI setup will adjust copy, ads and all other marketing processes based on performance, and report back on the best performing.
4. Remove the guesswork from your marketing campaigns
Marketing is not an exact science, as split testing and cold outreach show. Many campaigns are based on educated guesses, past experience, profiles, and other factors, which can sometimes be inaccurate in their utility.
A machine learning system that is robust can handle everything, from determining the best advertising channel to reach a particular audience to decide how much inventory is necessary to achieve specific sales targets.
Machine learning will be beneficial to other campaign components as well. Google’s Smart bidding system, for example, relies on machine learning, as well as many other AI content creation tools that are available to marketing departments.
5. Improved understanding of Audiences through Lead Scoring
It doesn’t matter if the campaign’s primary purpose is to raise awareness, build a brand or engage with the audience, the ROI of the investment is often the most important factor. Lead scoring, which is about determining how likely a lead will turn into a customer is one of the most time-consuming parts of a marketing plan.
Machine learning is a great help because it reduces labor costs and often assigns the highest scores possible to each lead in the database. This accuracy results in less effort wasted and significantly improved conversion rates.
Machine learning and artificial intelligence will transform many industries over the next few years. Marketing is no exception. It’s not a sector that is in imminent danger of being overtaken by computers. Instead, the benefits of new technologies mean that you spend less time analyzing data and guessing what your audience wants and more time delivering data-driven results.