In the modern world, marketing has become human-centric. As a result, there is an opinion that consumers have more rights than ever, but the same can be said about companies. Due to the many different types of data and information companies can create products and implement marketing programs that most accurately satisfy customer needs and provide a higher level of satisfaction.

According to Criteo, omnichannel retailers using online and offline data have 4 times more information to optimize their marketing efforts[1].At all points of contact modern companies can collect a large amount of marketing data about customers, which can be used to improve segmentation and build omnichannel marketing. Depending on the model of the user path map, a wide range of data sources can be used. For example, in digital space web analytics, social media analytics and session recording can be data sources. Offline contact points can be measured using quality research from customers and stakeholders.

IBM divides all customer information into 4 segments that answer 4 questions[2]

  1. Where? — interactive information (transcriptions of email messages or chat conversations, records in call centers, personal dialogs, web-click records);
  2. Who? — descriptive information (socio / demo / geographic information, user profiles);
  3. What? — behavioral information (history of orders, purchases, payments, use of the service);
  4. Why? — relative information (marketing research)

Based on different types of information, it is possible to form consumer profiles and build communications depending on customer profile. The use of this data can provide a significant advantage for increasing the relevance and personalization of marketing offers[3]

Sources:


[1]Criteo. Глобальный коммерческий отчет // Criteo. — URLhttps://www.criteo.com/wp-content/uploads/2018/04/17_GCR_Q4Report_Russia_RU_FINAL.pdf 

[2]IBM, Increasing Marketing ROI with Customer Analytics, // Fyisolutions. -URL: https://www.fyisolutions.com/_media/ibm_ba_summit_increase_marketing_roi_with_new_analytic_techniques.pdf

[3]Weber M., Improve omni-channel campaign segmentation with customer data // IBM. -URL: https://www.ibm.com/blogs/watson-customer-engagement/2014/11/03/improve-omni-channel-campaign-segmentation-customer-data/

7 комментариев

  1. The author of the article claims that today more than ever before companies have an opportunity to collect consumers’ information along the whole way of consumer journey in order to optimize their marketing efforts. I totally agree with this position. However, I suppose that there is a big gap between the perfect image of all the opportunities that companies have in the field of data collection and the reality. In most companies business processes are organized the way that doesn’t allow them to collect high-quality 360-degree data about consumers. Therefore, the implementation of CRM should be followed by the re-engineering of the existing business processes. That means that before planning to collect and analyze consumers’ data, companies should have clear perspective of how they would perform that on each stage.

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  2. I totally agree with the author of this article. Nowadays modern technologies enable business to collect a lot of useful information about the customer and their behavior. It gives company a great opportunity to organize their work in a more effective way. Today approximately all segments of IBM classification of customer information business get automatically and regularly, but we still have a «black box» — the fourth segment (Why?) — which takes a lot of efforts to collect and requires additional costs for the company, but it worth it. Because understanding of question why? opens a lot of hidden featers of consumer behaviour which can be used as a unique competetive advantages in a marketing strategy.

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  3. Anna, thank you for the post.
    I found the IBM classification of data by purpose very interesting. A lot of things aren’t clear, though. For example, why does “where” data describe interactive information if that information doesn’t include any place data? By this definition, if I have issues with my Internet connection and call the provider for help, our call recording is classified as “where” data? Instead, geographical information and GPS data is classified as “who” data. This is so confusing.
    I also wish you went into greater detail about which methods exist for data analysis based on customer data. In our course, we studied a figure that included five groups of methods for studying customers. Those are personalization, retention and loyalty, contextual marketing, acquisition and retention, and customer experience. You mentioned personalization in some detail, together with customer experience, but there’s much more to what customer data can give us.
    A problem with analyzing customer data is that it’s often unstructured. If we take one step beyond the purchase data, we can find great use in unstructured data, both internal and external, such as customer reviews, employee reports, internal documents and mail, review websites’ data and much more.

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  4. Anna’s article mentioned IBM’s data analysis. I believe this is the most important part and the essence of the article. The data analysis is divided into four parts, Where, Who, What, Why, and a simple analysis of them. What should be included. Modern society and related marketing technologies are well developed. Collecting information should be relatively easy for companies. But the more controversial, as the previous commenters have said, is the fourth point. The coverage of the fourth point is too large. Does the IMB’s data analysis suggest relevant solutions, such as how to collect this type of data.
    It would be great if these four points could be explained more carefully.

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  5. Gorokhova Daria

    I would also say that Analytical CRM helps not only to build customers profiles for further communication with segments but also helps in finding new clients for company. The process is quite similar to the process of targeting in digital campaigns when you use LAL (or look alike segments). You understand how current clients behave (for example, you realize that 75% of most valuable for you client come from search engine advertising) and it allows you to adapt marketing expenditures in communication with this segment. Moreover, you can use aggregated characteristics while building targeting in digital to make advertising much more efficient and find the correct route to the desired segment.

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  6. Мария Французова

    Post describes only the positive aspects of personal offers for customers. But what about negative aspects? Not all methods of collecting data from customers and their further analysis are legal. Many companies sell databases to those who need it. Often, consumer rights are violated. Russia has laws ensuring the safety of citizens: The policy for the processing of personal data is developed in accordance with the Federal Law of 07.27.2006. No. 152-FZ “On Personal Data” (hereinafter — FZ-152). But not everyone complies with these laws, and tracking this is quite difficult.

    Sources:
    Modelling CRM in a social media age
    Australasian Marketing Journal (AMJ), Volume 23, Issue 1, February 2015, Pages 27-37
    Paul Harrigan, Geoff Soutar, Musfiq Mannan Choudhury, Michelle Lowe

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  7. Павел Сивов

    It is necessary to add about the differences between the systems. Unlike operating systems, analytical ones not only record the history of interaction with the client, but also help to trace the patterns in sales: customers from which sources buy most often, at what stage most transactions break down, how customers are distributed across the sales funnel.

    Examples of analytic CRM are products from SAS, SAP BusinessObjects, and Marketing Analytic.

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