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This is the third part of our series "Digitalisation 2021". After looking at the areas of sales and IT security in the first two articles, we take a closer look at the digitisation of marketing in this article. The upcoming parts will be about logistics, finance, procurement, manufacturing and controlling. The subject at hand is marketing automation.
A practical example - let's take a look at the current job ads for Marketing Automation at Zalando (as of 03/27/2021).
Out of the first eight matches displayed, seven ads show a purely technical nature, and only one product manager appears here. Taking a look at this job description in turn, it's also about "automation, analytics, and machine learning." The trend is obvious. Technology has made its way deeply into marketing, and artificial intelligence is already replacing the first jobs in the field.
Zalando was one of the first companies to recognize the importance of data-driven decisions and started early to dovetail data and their IT with their marketing. However, marketing automation solutions are not only reserved for large companies, SMEs can also benefit significantly from digital marketing solutions. Prices have become affordable and the potential is enormous, particularly with regard to new customer acquisition. This alone quickly recoups investment costs. So let's first take a look at what marketing automation is. Then we'll look at the next stage in the development of marketing digitization: artificial intelligence.
What is Marketing Automation?
The name already suggests that Marketing Automation is a software to automate marketing actions, and in the course of this also to schedule and execute them accordingly. These marketing actions are, for example, repetitive tasks such as sending emails, interactions through social media or on websites. One classic example here is the chatbot. Marketing campaigns can be implemented efficiently with automation and companies can also measure the success of the individual marketing measures. In summary, marketing automation allows ways of acquiring customers, retaining them and analyzing the customer relationship by collecting information about them. Marketing automation bridges the gap between marketing and sales with the aim of improving the collaboration.
Key features of Marketing Automation
There is a range of vendors for marketing automation tools. Below we summarize the most important features that can significantly improve your marketing, making it efficient and reducing costly manual activities.
Lead Management
In sales and marketing, a lead is a prospective customer who has provided the company with his or her contact details. In other words, a potential buyer. Lead management encompasses all activities that take care of the lead until it is ready to make a purchase.
Lead Capturing & Lead Generation
Acquiring new leads is called lead capturing or lead generation. A classic method of marketing automation is to get a website visitor's email address in exchange for free and useful information for them, e.g. in the form of a PDF file. Chatbots and email marketing are also used for lead generation.
Lead Scoring & Profiling
During the next step, it makes sense to determine the potential interest of the lead in the products or services - known as lead scoring. The rule is: the higher the score, the higher the lead's willingness to buy. Thus, the results are important insights for the sales department, which can convert qualified leads into buyers and customers more efficiently.
Lead scoring & profiling also helps to better understand one's target audience and therefore concentrating marketing investments on the most promising leads and increasing the return on investment (ROI).
Lead Nurturing
If a lead is not yet completely convinced of the product or service, a lead nurturing campaign comes into play. Here, you provide the respective leads with valuable information or special offers that accelerate their decision to make a purchase. In addition, the relationship with these potential customers is deepened.
Behaviour Tracking
Marketing automation can also be used to track the behavior of customers or visitors at specific touchpoints (e.g., website, email, social media). This is referred to as the "customer journey", i.e. the individual cycles a customer goes through before deciding to buy a product. You can capture how a visitor behaves on a website, whether they open an email or even their identity as soon as they log into the website. This would be different from, for example, Google Analytics, which records the behavior of a collective group of anonymous visitors, while Marketing Automation can link information to a specific person
Workflows
Workflows are an integral part of effective marketing automation. You can think of these workflows as a rule-based schedule that is started by a trigger.
Workflows are applied to all areas of marketing automation, especially lead nurturing, lead generation, and the creation and management of omnichannel campaigns. The key here is the software's ability to communicate with third-party systems and tools. This is where it is often decided to develop own solutions or interfaces to meet the individuality of each company.
Personalized content & targeting
Customized and individualized content is what the customer wants. And it is becoming increasingly important to use highly relevant content. Because targeted personalization increases customer satisfaction and thus customer loyalty. Often, customized campaigns are sent with the right targeting at the right timing, but fail because the content is less relevant. Insights into the success or failure of such campaigns are gained thanks to analysis of open, click, and conversion rates.
Analytics & Prediction
As we reported in the first article, data analysis can be used to optimize processes and operational procedures within a company or to discover trends and new market opportunities. Analytics in marketing automation shows results of marketing activities and provides conclusions on how to intensify customer relationships. In this case, we are talking about descriptive analysis, which means the evaluation of past-related data. In predictive analytics, data and predictive analyses can be used to look into the future (e.g. predicting customer behavior). This is purely statistical. If you combine the whole thing with artificial intelligence, you reach the next level - the prediction of developments. Not without reason, predictive analytics is one of the most hyped marketing topics. However, such calculations are complex and demanding of resources and require strong expertise in performing data analyses.
Artificial intelligence in marketing automation
Artificial intelligence (AI) is on the rise in marketing, as we described at the beginning of this article. Now what happens when this technology cleverly joins forces with marketing automation?
Artificial intelligence takes many of the previously described functions of marketing automation to the next level (often enabling the services of marketing automation in the first place). In other words, higher precision and more efficiency in lead management, customer targeting, the delivery of personalized and individualized content, and especially in prediction and analysis.
When it comes to analysis, AI is ideally suited to analyzing the existing customer base, reactivating inactive customers and using the insights gained to automatically and precisely optimize the customer experience of all customers. And all this in just a few moments.
AI algorithms provide much more precise information about when, how and by which marketing measure a lead or customer buys, stays or returns. These insights can be used to derive patterns and, above all, customer segments, which in turn qualify for marketing initiatives such as advertising campaigns.
Real-Time Marketing
From now on, campaigns are no longer rigid automation routes, but dynamic and tailored to user behavior in real time. Just like artificial intelligence, they become "smarter" with every interaction - and thus better in every respect, whether it's closing a sale or maintaining a customer relationship.
Conclusion
The digitalization in marketing through marketing automation has fully arrived on the market. Affordable software solutions enable SMEs to use automation in a way that was previously only permitted to large corporations.
Now, it's time to fully explore the vast and profound possibilities of AI. As Gartner also notes in its latest Digital Marketing Hype Cycle for 2020, real-time marketing and AI for marketing are among the top five technologies of high importance to marketers. However, AI represents a long and steep learning curve for marketing, with two key challenges for marketers before it can be mastered: first, the availability of data in terms of both quantity and quality, and second, the qualification of the workforce for this area.
The impact of AI will not only increase in marketing, but in all areas of the business world and in private life as well. So start early to build a team of specialists in data science, machine learning, artificial intelligence, deep learning, and cloud computing.
This was the third part of our series "Digitalization 2021". Learn about the importance of Digital Transformation in logistics in the next article.
Part 1: Digitalization in sales
Part 2: Digitalization of IT-Security
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