Brands selling similar products and services can differentiate themselves purely by the quality of their customers' experiences. Machine Learning helps to deliver a superior customer experience.
For example, take Netflix which has over 100 million members has had to go beyond rating prediction and into customized ranking, image selection, search, messaging, and much more.
They use machine learning to suggest content that the viewer is most likely to enjoy, based on everything they before watched, ignored, and rated. Marketers can leverage the strategy adopted by Netflix to optimize and to boost overall engagement metrics.
The common thread among all of them is the use of machine learning to manage customer journeys across various digital experiences in a way that maximizes the experiential value and thus engagement.
Advertising is a major cost for digital marketers. Traditional campaign optimization is based on manual decision-making such as:
Which advertisement channel to choose
How much ad space inventory to buy
The timing of the advertisement
The duration of the ad campaign
Of course, like all manual processes, this process’s effectiveness is constrained by the human limitations of brainwork and number crunching.
Leveraging the power of machine learning can optimize the performance of your existing marketing campaigns.
ML-powered email marketing can help leverage nuanced customer segments and personas, a library of content, and data about prospects. The result? Marketers can hyper-personalize their email campaigns with ease.
Here are four ways machine learning specifically helps marketers improve email campaign effectiveness:
Content creation: Writing tailor-made subject lines and messages to help drive user engagement (what to send).
Data segmentation: Defining rules for sending emails to prospects (whom to send to).
Timing: Using previous responses to determine the right timing for sending emails to prospects (when to send).
Delivery: Enhancing the reputation of the sending domain, to ensure the reliable delivery of all emails (how to send).
Apart from this, machine learning also allows marketers build split testing right into email marketing.
Research suggests that 79% of customers prefer to live chat or getting their questions answered quickly. Here are the benefits of customer service chatbots:
Zero customer wait time
Ever-expanding knowledge database
Plus they have the ability to route complex queries to human counterparts
And it's not just customer service where chatbots shine; they can even assist brands with outbound marketing by sending follow-up messages to customers.
Web design, although instrumental for successful digital marketing, is a major problem for marketers. But machine learning is a lifesaver, as it can bring together data that is related to user preferences, website heat maps, design best practices, and A/B tests.
The result is You can create web designs based on a lot more practical data, rather than on a designer’s guesswork.
AI-powered design assistant tools help human designers create superlative web designs.
The results of using such tools can be pretty amazing which, of course, makes for better customer engagement.
Brands that manage the user experience with marketing automation tools achieve a 451% higher qualified leads rate:
Brands that manage their leads using tools for marketing automation experience 10%+ revenue rate jump after 6-9 months.
49% of businesses use marketing tools for their email automation.
79% of renowned brands have used tools for marketing automation for over 3 years.
Marketing automation takes your strategy to the next level. It uses machine learning to crunch numbers, learn from patterns and past outcomes, and deliver dependable insights – on customer segmentation, prescriptive suggestions, content targeting, and follow-ups – that simplify your decision making. As it keeps learning, it keeps getting better. That’s your entire marketing value chain, automated, in principle.