Customer Analytics in Focus

Why is customer analytics so important? In the economic realities, with ever-increasing competition, only the player will survive who knows his client better and knows how to make managerial decisions based on data. In this case, you need to know the measure.

Remember the famous joke? Two people in the forest saw a tiger rushing at them. The first calmly changes into sneakers. The second one in horror asks: are you going to run faster than a tiger? No, the first answers, it’s enough for me to run faster than you ...

In the modern world of Big Data and Data Driven Companies, in order to succeed, it is not necessary to own the entire amount of data (which increases significantly when you read this note) and use all the tools - just run after your client faster and smarter than your competitor. Many companies succeed in this, not paying attention to the possibilities of new customer data. They cross their Blue oceans at a speed far exceeding that of the Titanic. But there are risks ...

In this context, as an exchange of experience, I would like to share my thoughts on client analytics: why is it needed, how is it related to marketing and sales, what are its connections with the BI (Business Intelligence) and RTM (Route to Market), and how it influences organization and its culture.

1. To see The Customer

Getting a customer is the goal of any business, which is then converted into revenue, market share, ROI and other important metrics. The more accurately you define your client at the level of Vision and Mission of the company, the more accurate your strategy will be. And here you can not do without a serious analysis, using related tools. Thus, customer analytics is an integral part of the strategy, influencing the priorities, goals and directions of the company.

On the other hand, having decided on big goals, you will definitely move on to tactical tasks: how to attract new customers and retain existing ones, how to ensure up-sale and cross-sale, level of satisfaction; in terms of product or service offer - how to optimize products and their offer; in terms of channels and promotion, how to enter new markets and effectively improve your position in relation to competitors. These are the main operational tasks of client analytics.

2. BI or not-BI 

It is important to immediately distinguish between Business Intelligence (BI) and client analytics. Business Intelligence - these are general methods of translating business information into a meaningful form for making management decisions, which include not only client analysis, but also many internal processes of the organization: technical KPIs, budgeting, rolling forecasts of internal efficiency, etc.

In this sense, traditionally BI is a general category and a more general toolkit; client analytics is a necessary component of it. It is effective when it combines all external and internal data for the necessary adjustment of strategic and organizational actions: distribution of investments, capital, resources, managerial focus, etc. Drawing an analogy, one can compare BI with the integral function of the brain, which should not only see the specific purpose of its activity , but also constantly monitor all the parameters of life: temperature, pulse and other hundreds of thousands of indicators, without which it is impossible to achieve goals.

Further, when analyzing tactical tasks, client analytics should always correspond to the chosen strategy; when setting goals for analysis, strategic or business goals should be paramount. Analysis is a laborious task, and as an expensive resource it should be used where it clearly brings money (due to the flow of customers, increasing market share, etc.) or saves resources. There is no need for theoretical research at the expense of a market company. There are special institutions for basic research.

3. What is good

Good analytics will satisfy the need for optimal decisions. But the needs are limited by the knowledge and capabilities of the leader. Moreover, these are high-level limitations, since, as we found out, such analytics is strategic in nature. In other words, in order to do this really cool, the organization needs to accumulate knowledge: what additional data about the client may be available, where to store it, how and for what purpose to analyze, how to apply. An important question: where should the competence center itself be located? This feature is gradually moving away from traditional marketing, which previously had not used IT infrastructure at all, to technology marketing - for example, in online sales, where it is 95% dependent on IT.

The world is becoming faster and the amount of data is larger, therefore, to realize its competitive advantages it is impossible to concentrate the skill of analytics in one place. Applied business analytics should be part of the organizational culture of the company. It is recommended to carry out comprehensive events to exchange ideas, experiences, best practices in the field of analytics and decision making based on reliable data. This approach is expressed in the fashion phrase «Data Driven Company».

4. Imagine the data 

You need to not only be able to analyze, but also be able to visualize, quickly and clearly. Here I can recommend tools like QlikView or Tableau. Even regular Excel in experienced hands can work wonders. Each application has its pros and cons, but you will be surprised how much the possibilities of Excel seem limited to you if your employees can switch, for example, to QlikView.

Of course, this work will require some preparation (although each of the vendors will tell you about the intuitive interface), and you need to first think about what tasks the company faces and whether it needs additional tools. It’s important that people in the organization do not spray on learning many tools at once. Choose one and teach key employees to work with it.

5. Conclusions based on the numbers 

I will give a simple example from practice. We analyze the traffic from landing pages, see if the conversion has changed. I hear the analytic’s voice - «yes, it grew, yesterday it was 6.2%, and today it is already 6.8%». It would seem that there is a result, but I decide to clarify - «whether these two indicators differ from each other?» She answers me that the conversions differ by 0.6% (almost 10% growth, excellent!). However, after a more careful analysis of variances, it turns out that the values were not statistically different from each other.

You can repeat this experiment in your company and make sure that 50% of the data in the reports of specialists with higher education that you use for daily decision-making suffer from the same drawback. Most likely, you will hear that there is no need to calculate more precisely, since these values are quite correct, and the reports you read are much better than those of competitors. And thanks to them, you make brilliant marketing decisions that lead to profit growth. Attention, the question is: is this really so? Maybe the profit could be greater, but the solutions could be more accurate? These issues are especially important for a business that exists in an ever-changing environment where serious changes can occur hourly, where it is necessary to make corrective decisions - of course, based not only on intuition, but also on objective analytical data.

6. From Small to Large 

The amount of data available is growing exponentially. It is not important how you call it - Big Data or Small Data, you need the skill to use them. Do not bother with what category they belong to - just get them, store, analyze, draw conclusions and apply in your work. You can start with setting goals and objectives of the upper level, and then proceed to consider the state of client analytics and develop measures to improve it. Since, as a rule, the client is the cornerstone of the strategy, the analysis of the client’s data is the first priority.

The action plan should be supported by the first person - CEO - of the organization, become a priority for different departments (marketing, retail, IT, back office, etc.). In my opinion, the role of CEO is critical. Among the vivid living examples Tim Cook (Apple), Jeff Bezos (Amazon), Mark Zuckerberg (Facebook), you name them. I should mention the “dancing green elephant” - Sberbank, headed by Herman Gref. The inspirational and transforming energy coming from the leaders of these companies is a good example.

7. Ask questions 

Even if you are running faster than a competitor, you can always find what to improve. You can do something new, you can stop doing unnecessary things, you can do something differently.

Who are your customers? How many of them? What are their incomes? Imagine your target customer: how he will change in three to four years, his habits and preferences. Is he the focus of your strategy? Surprisingly, many managers cannot clearly answer these questions. And when we assume that the answers to them are known, after a few iterations we can find that, unfortunately, not everything is so clear ... 

Often we work simply with those who chose us for non-transparent reasons. It reminds a joke about a man who lost his watch, but searches for it not where he lost it, but where it is lighter and more convenient to search. Often we do not adjust our actions, starting from the forecast, but simply work “on the thumb”.

Analyze what your current customers spend time contacting with your organization. How many products and services they actually receive at these moments, and how much they can potentially get.

Analyze: where and how customers meet with your organization - at points of sale, in a call center, on a site, on a web-site, inside the app, through agents, etc. In many companies, this work is not systematized. Most likely, it turns out that you spend a lot of money on providing supporting functions, and you do not pay enough attention to sales at points of contact. See if the entire product line can be offered at any point of contact? How are your products offered at this moment? What can be done to identify and meet customer needs?

It is also important to try to assess whether the share of sales through the channel meets market standards. For example, if the average retailer has an online sales share of 20% across the industry, then why do you have less? If the share of mobile traffic within online is already almost 70%, then why do you have only 25%? Etc. If mobile traffic shows good growth dynamics, answer your question, have you allocated resources for your growth in this channel? Here the numbers are again needed.

8. Write more 

In our practice, we wondered: is it worth storing all the data received? When I visited Silicon Valley last year, I saw examples of companies that, from just-written data on client behavior, after a few years were able to learn how to get managerial benefits and eventually began to sell many times more. Record everything you know about the customer. Today there is no problem with data storage, its cost is small, especially if you do not store the results of intermediate calculations and models, but only verified data from the original sources. If you are told that it is expensive, then you are storing something wrong or wrong.

A company can have several software and hardware systems at the same time on its own or cloud servers. Write somewhere - to where your analysts can quickly extract information for analysis. The Single Source of Truth principle is useful here, when the same reliable data is stored safely only in one place with the ability to read from another. A simple task that is solved at the level of data storage policy. It is important here not to create additional difficulties for yourself. And do not make it difficult for analysts and managers to obtain data if their request is justified by business tasks.

9. Predict more, accurately 

When it comes to a long-term forecast, try asking your specialist: what data is taken as the basis of the analysis? How were they obtained, primary or secondary, are they not defective, where were they stored? Have they been standardized? How was the model built? You will learn (or maybe not) a lot of new things.

Ask the direction director: does he even know the basic principles of data aggregation, placement and standardization? Does he know how to work with unstructured data? How to draw statistically valid conclusions and build probabilistic models?

Studies show that marketers and sellers are constantly “not catching up” with the market in this direction. New technologies are difficult to adapt due to the slowness and conservatism of IT. 

The amount of available data increases many times a year, and the amount of analyzed client information grows only by 10%. What kind of forecast quality can we talk about if many do not even know what data and technologies are generally available ...

Often, when you receive a customer analysis, you come across “just numbers,” a report in the format “as you requested.” It is more efficient to set the task to prepare preliminary results of the analysis so that the employee who prepared the statistics finds patterns, trends that will outline possible actions to achieve business results. In preparing the report, the specialist must understand why this material is being prepared, and each time find reasonable opportunities for sales growth, indicators of changes in consumer demand or changes in needs. You do not need analytics without recommendations.

9. Omnichannel, cross-functional 

Omnichannel marketing is a fashionable and easy-to-use direction: after a short test, you can easily decide which communication channel to use, to what extent and at what cost. 

Constantly test channels: messengers, social networks, emails, sms, etc., scale them - of course, if it is justified. Be innovative; for example, if you offer payment terminals, then change the expensive traditional POS terminal to an inexpensive mobile mPOS solution, and in addition to the basic service, you can offer a geolocation marketing service for your B2B clients. 

You can easily balance the communication mix using purchased or your own platforms and programs: send messages only to those customers who really need them, on those devices and through the channel that is best suited for this. Do not spray. Remember the 80/20 principle - choose a small number of groups / channels with great potential and deal with them first of all.

10. Can I outsource client analytics?

I believe that you can give everything to external executors, except the strategy - it is up to you. Accordingly, you can store any data on foreign servers, process it there. Naturally, there will remain issues of safe storage and transmission of data, methods and methods for their storage, preparation - but the approaches to the solution are clear. You can hire third-party processing, modeling and forecasting specialists: most likely, it will be cheaper than creating and preparing your own team. But only if your managers and IT specialists are able to set goals and organize such work with partners. It is important that you set the tasks, and you make all decisions on the use of data to improve your client performance.

In the modern organization, the role of fast design multifunctional teams created to solve a specific applied problem is growing. Obviously, to solve any client problem, both marketing and sales are required, and technology plays an increasingly important role - both IT itself and organizational technology. If there is no culture of cross-functional interaction, if there is no practical experience and project management technologies, client analytics will be weak, "sluggish" and ultimately ineffective. That's why you need to pay attention to this corporate problem at the highest level.

In summary, 

I’ll say that when implementing your strategy, you always move towards your client. The better you know him or her, the better decisions you make - in the strategic, medium and daily horizon. Systematically build the competencies of customer analysis in the organization. There is more and more customer data, and this gives undeniable competitive advantages to those who can use it.

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