Linking analytical and operational CRM: how it works and who fits it

The CRM system is a familiar product that is used in almost every business. Companies buy additional analytics blocks and applications, integrate CRM with business intelligence systems, and some are even thinking about using advanced analytics technologies, such as Big Data, Machine Learning, Data Mining – all with one goal – to get more useful and actionable information from existing accumulated and historical data. Also remember that you can always order services moving and storage company software.

But in fact there are two types of CRM-systems – analytical (ACRM) and operational (OCRM). A few years ago, and often even now, when the word CRM-system, most customers imagine the operational type of systems. These solutions provide direct interaction with customers and leads. However, if both types of solutions are used competently in conjunction, it is possible to solve much more complex business problems and get non-trivial results.

The idea to link the two CRM solutions originated in the financial industry, where the number of customers and products is high, the competition is high, and you have to experiment to change things. Since then, a lot of time has passed and similar solutions have started to be used in other industries. In this article, I will look at the impact of this integration on the highly competitive and IT-dependent transportation market.

Specifics of the systems

The task of operational CRM is to help businesses interact with customers one-on-one, whether it’s through email, personal interaction with a salesperson, or some other method. An analytics system monitors customer interactions before and after contact-that is, it lets you understand how to communicate with a particular customer. With built-in behavior analysis solutions, it lets you know that one group of contacts is already very loyal and only needs to be maintained, while those customers need to be dealt with very tightly because they are dissatisfied and will soon leave.

Analytical CRM-system is, more often than not, an addition to the operational, rarely the client needs only an analytical solution, because it does not contain tools for working with clients. But it is not a classic solution for analyzing business metrics. Analytic CRM-system, depending on the objectives of the business, contains elements of BI, tools for collecting data from different sources, Data Mining, analytical cubes, tools for building predictive models and other tools for in-depth analytics.

In simple terms, the operational CRM system is the front end, which is used by those who directly interact with customers on a daily basis: managers, salespeople, salespeople and marketers during campaigns. The analytical CRM system is the back office, used by analysts, marketers, PR specialists – those who do not interact with the client all the time.

Bundling is most effective in industries where data volumes are particularly high, for example, a lot of customers, or, conversely, few customers but a lot of services. Both of these situations are found in the transportation industry.

How to use in the transportation industry

The transportation market is one of those areas where a more data-driven approach is almost necessary to compete and grow. There are a lot of cargo, passengers and services, and you need to interact with all customers and offer the best possible service.

Outflow model

Let me start with an example. It’s very interesting how this connection works from the point of view of the churn model. For one of our clients, we solved a typical problem of modern transportation companies – customer churn. That said, in the transportation industry, not only can a client leave to another provider of the same service, switching to another mode of transportation is a much more popular difficulty and more critical, because the entire industry falls in mass switching.

To prevent this from happening, the analytical part of the CRM-system develops a model of customer behavior to prevent churn. To do this, the period when the client who has not bought a ticket is considered a “churn” and, using mathematical rules, calculates the probability of transition of the client from loyal to “churn”. Then these rules and models are applied to the whole client base, for each client the period when he can move to the group of “churn” is set.

The operational part of the CRM-system is used to influence the group “otchetnikov” as follows: it monitors the process and adds customers to a specific list, which helps pinpoint interaction with a particular group – to give extra points, to offer a higher class, for freight companies, for example, one of the most effective incentives – this discount. Then with a letter, a call, or any other channel, you need to get that information to the customer.

Marketing campaign lifecycle automation

Another interesting task is to automate the entire life cycle of a campaign – from setting strategic goals and forming customer segments to data collection and analytics. In this case, an analytical CRM-system builds a model under which marketing lists are selected, the base is segmented, exclusion lists are formed that will prevent annoy customers who unsubscribe from frequent contact with you, cluster analysis and search for similar users in the base is done.

The next step – all this information is transmitted to the operational CRM-system, where lists of clients are created, tied to a specific campaign, channels – and then the impact itself is carried out. An important subtlety here is that the system must be integrated with all communication channels – website, mailing programs, call center. In this case, additional features such as generators of landing pages may be in the CRM-system, as well as in these applications, for example, mailing systems. All modern providers, like ClickDimensions or MailChimp, offer such tools. You can use them to solve additional tasks not directly related to sales. For example, at RUSCON we automated the customer satisfaction survey on the Microsoft Dynamics CRM platform.

The last step is the evaluation of feedback. We need to analyze whether there were purchases, in what volume, whether the check increased, whether the behavior of the customers we were targeting changed, and in what direction. If the goal of the campaign is to increase loyalty, then on the basis of the information on the tickets purchased it is possible to understand how effective the campaign was. The analytics part of the system can do analysis on the number of tickets sold, transactions recorded, pauses between trips, and other metrics.

Technologies are developing rapidly, but not all of them are used by businesses. The topic of ACRM and OCRM is little discussed in Runet, although it can do a lot – reduce churn, increase loyalty, increase the average check or frequency of service use. I hope more and more companies will delve deeper into experiments with marketing and sales and squeeze the most out of the available IT tools.

Comments are closed.