Why Marketing Cannot Ignore Modern Technology
Now is a great time to work in the marketing department, as in the modern information world, marketing is becoming increasingly important in most organizations. But it also means that the life of the marketer has become more complicated, despite all the tools at his disposal.
Marketing specialists have to solve many problems:
- how to get ahead in the conditions of fierce competition;
- how to increase customer loyalty;
- reorientation of a business from a product to a client;
- the saturation of social networks, where everyone is now a content provider;
- how to better understand the buyer;
- how to justify the return on investment within the company;
- how to keep up with technology, etc.
The list goes on and on. In the world of marketing, it is usually clear what needs to be done, especially when you are cooperating with experts, but it is not always clear how to do this optimally.
Yes, and the solution to some problems will tell machine learning, it's time to think about it seriously! As we move from a hypothesized world to a data-based world, we realize that theories are no longer needed.
Practical decisions need to be based on data. We do not mean reading and digesting hundreds of reports myself. We say the data, the results of the analysis of which will give you a guide to specific actions, and this can only be achieved using machine learning.
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The Benefits of Machine Learning
Technology does not stand still, more and more processes are being automated - which used to be substantial human labor costs can now be done by a computer. Machine learning is the ability to replace human labor with machine labor. What are its advantages?
1. High-speed response time. The machine checks any hypotheses much faster and, after implementing the algorithm, issues solutions in real-time.
2. Machine learning technologies are a flexible tool that is suitable for solving problems of a particular business, and a model is created individually for each case.
3. Using machine learning reduces staff costs and customer acquisition.
4. Much more data is processed in less time. A person is physically unable to handle such a volume of data that a computer can efficiently process. Moreover, information is usually updated continuously, which makes the processing process endless and continuous.
5. Marketing processes are automated and do not require constant human intervention. Moreover, the longer the machine works on a specific task, the more successful its solutions become and the higher the conversion.
6. The machine takes into account an incredible set of factors based on which it makes a decision — the parameters on which it should be based and can be changed continuously depending on the task.
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How to Incorporate Machine Learning into Your Marketing Strategy Properly?
The incorporation of machine learning technologies in a particular business is carried out in two scenarios.
1. The first scenario is the introduction of a unique set of classical algorithms that have already been tried many times, optimized, and showed good results. For each client's task, we already have ready-made solutions that have a certain percentage of accuracy and degree of success. Each model has its degree of probability of completing a job, so even a standard scheme of actions is suitable for improving the results.
2. The second scenario is a more flexible and sophisticated algorithm that a machine must follow to solve the problems of a particular client. Such a situation involves not just a set of tools that have proven themselves well in practice with other customers, but an in-depth and detailed study of the model for a specific client and his tasks.
How Can Machine Learning Help Marketers to Boost Their Business?
If you are still puzzling how to integrate machine learning into your marketing, this part of the article is for you. Four simple ways will help you get started tomorrow.
1. Prompt response to the needs and demands of the audience
Machine learning technologies allow you to collect customer data in real-time: what kind of purchase a person just made, how he reacted to the newsletter, what kind of feedback he left about the company, etc. Up-to-date data helps managers make effective decisions, and marketers help them respond as quickly as possible to the needs and demands of the audience.
2. Customer Profitability Forecast
Analyzing data on customer behavior, ML-programs predict loyalty, "life span" of a particular client. Thus, you will find out which buyers should invest more time, effort, and money. Besides, such programs allow you to simulate "what if" scenarios (how will a specific segment of the audience behave if we make it a particular offer?) And derive success formulas.
3. Customer segmentation to create personalized offers
Yesterday, business opportunities were limited to stingy data only on the gender, age, and purchases of the client. Machine learning allows you to collect and analyze data simultaneously from several sources: behavior on the site, reviews, and discussions on social networks, purchases, etc. Thanks to this knowledge, you can assign clients to groups / segments (for example, beer lovers, young mothers) and develop an individual proposal for each group ("buy a bottle of beer and get a second as a gift", "only today a large package of diapers for a small price" ) You can talk about promotional offers in SMS or e-mail newsletter.
4. Improving the quality of service through direct communications
Analyzing data on customer actions in the past, ML-programs form recommendations: when you need to contact one or another customer, which channel is best used for this, what exactly to offer/ask. Sources of such data may be call center, web analytics, etc.
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Additional Advantages That Can Improve Your Business
Anticipating customer needs is far from a new phenomenon. Qualitatively unique is the ability to automatically respond to these needs in real-time and on a full-scale thanks to machine learning. The most common examples of using ML in marketing are:
- Testing the many possible routes that consumers can follow after using the content;
- Purchase programmable advertising;
- Optimization of customer interest through personalization of content;
- Preliminary assessment of potential customers.
- Search and forecasting of the most and least valuable customers in terms of LTV or their "life cycle";
- Creating images based on client clusters and generating appropriate content and services for them;
- The recommendation of new products and content with the most significant prospects for the purchase;
Conclusion
You need to understand that ML is something that will soon become the standard for automation systems of any client business. Analysis of preferences, advanced audience segmentation, and dynamic pricing are the three pillars on which the event industry will be supported shortly. For many domestic entrepreneurs, machine learning is something futuristic and far from existing business realities. It is a working and cost-effective tool that can not only improve your business but add comfort to your customers.