What does Machine Learning Mean for Marketing Automation
One of the biggest challenges that marketers face is how to personalize emails to individual prospects and customers. It can be rather difficult to sort through and process tremendous amounts of data coming from multiple sources. Data on purchase behaviour, number of website visitors, and mobile app usage – to name a few. With machine learning, automation is becoming much easier. “Now ML driven marketing can start with the customer: her history, interests, current context, and journey with the product before selecting the right message to drive engagement at the right time. This is an exciting shift that will continue to transform the field” said Mike Tamir, Head of Data Science at Uber ATG.
Unlocking the power of big data
Machine learning in marketing automation serves one purpose: to make your life as a marketer much easier. It helps you to focus on the most relevant data and to make accurate, next-best-action predictions. This, in turn, puts you in the position to increase productivity, engagement, and customer loyalty. Not to mention receiving a return on investment of your campaign.
Here are 5 ways in which machine learning can truly transform your marketing workflow:
1. Making better use of big data – As things stand, manually analyzing large volumes of data takes a lot of time and effort. Then, you have to apply the most important element: context. Data means nothing without context.
By automating the data collection and analysis process, there is no limit to the amount of data you can handle. From demographics and preferences to clickstreams and social media activity, machine learning allows you to measure the future value of your business and to predict growth.
2. Segmenting customers – Did you know that only 25% of companies are effectively using data to generate better customer experiences? One way in which you can use machine learning to your advantage is by segmenting customers.
Customer segmentation models are used to divide customers into small groups of individuals with similar preferences, needs, and behaviours. Successful customer segmentation predicts how customers react to your service, thereby allowing you to make better strategic marketing decisions. And as a result, enhance the overall customer experience.
3. Predicting trends – Machine learning draws patterns from previously gathered data and then applies it to everything it collects from then on. As a marketer, it opens the door to predicting trends down the road and preventing possible negative outcomes. For instance, the system can target prospects within a certain demographic that are twice as likely to purchase your products or services. Combined with marketing automation, the chances of converting these prospects into customers is high.
4. Establishing sales – Machine learning utilizes big data to deliver your sales team with the most relevant content for each sales opportunity. This, in turn, helps to ensure the buyer’s journey runs as smoothly as possible.
“Understanding what motivates a consumer, how a consumer signals their intentions and interests, what turns off a consumer, what conditions induce a consumer to make a decision, etc. are all part of behavioural sciences. Predictive marketing models help to answer the question “what is the consumer likely to do next?”, and prescriptive marketing models help to answer the question “how can we achieve a better, optimal outcome in this situation, hopefully producing a win-win for the consumer and for the business?” said Kirk Borne, Principal Data Scientist and Executive Advisor at Booz Allen Hamilton. As your algorithms ‘learn’, your marketing offers and incentives will become better than ever.
5. Eliminating the hassle of repetitive technical SEO tasks – Setting heights and widths, compressing file sizes, and all other types of repetitive tasks – Sound familiar? Now, machine learning is automating technical SEO tasks so that you have more time to spend on creating content. Additionally, automated reporting and audits allow you to target technical issues faster and even predict them before they occur.
Moving into the next phase of data-driven marketing
Machine learning software has come a long way. New algorithms are constantly surfacing, driving at new applications and possibilities. With their help, computers are now independently finding solutions to new, previously unknown problems.
Regardless, most of you may be reluctant to use any form of machine learning in your everyday efforts. This is likely because machine learning remains a complex field, requiring the participation of data scientists and developers. However, easy-to-use specialized applications have been developed to address these marketing challenges. Now, you can focus more of your time on quality strategic marketing decisions and less time worrying about their execution.
In today’s marketing world, machine learning is already a ‘game changer’. It enables new levels of interaction between businesses and customers. However, we have yet to see its true potential for improving the efficiency and effectiveness of teams and campaigns. As a marketing tool, it will prove its value going into the future as it becomes adopted across more industries.
“Machine learning is being baked into everything because it is the only viable way to get a handle on the volume of Big Data that is overwhelming every business. This presents marketers with both a challenge and an opportunity. The challenge is fairly simple: understand what machine learning has to offer in the first instance. The opportunity is humongous: articulate what you want to extract from the data you harvest and use machine learning tools to help you do it” said David Amerland, a business journalist.
There is no doubt about the fact that machine learning and marketing automation go hand in hand. Machine learning is revolutionizing the way you use MA systems, moving you toward a more strategic position as a marketer. It’s the dawn of a new era and in the coming years, one thing is for sure: we can expect great things.