What Metrics Should You Include in Analytics Dashboards in 2019

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Content
1. Graph of connectivity of goods
2. Price cascade
3. BCG scoring model
4. Multi-channel attribution
5. RFM chart
6. Replenishment revenue charts
Russian business is entering a phase of fascination with telegram db analytics. Entrepreneurs, after getting acquainted with BI systems and dashboards, are making plans for amazing growth as a result of implementing business analytics tools.

Management dashboards are a truly useful tool that allows you to make informed decisions at a variety of levels. A large number of companies in the country already analyze their own revenue in detail. Some have even moved to the so-called second level of analytics, working with more complex and non-obvious indicators. For example, UIS end-to-end analytics allows you to track advertising, marketing, and key business indicators, as well as build a sales funnel that clearly shows which sales channels work better and at what stage.

However, an analytical dashboard can also cover other, more interesting metrics, graphs that are relevant to any business. They can be obtained from the results of the sales database analysis.

We propose to consider examples of such non-standard graphs within the framework of this article.

Note that the list of graphs under consideration does not include those based on the results of a priori data analysis. These are, for example, visualizations of customer survey results. The standard set of graphs for revenue analysis is also not considered here — the presented metrics are aimed at implementing high-level analytics in order to optimize implicit business risks.

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1. Graph of connectivity of goods
It will allow better assessment of the compatibility of different product groups in dynamics based on the results of the assessment of the user experience of making a purchase decision and flexible management of second- and third-level merchandising in the future, helping the procurement department employees to form inventories.

The chart below, created in Microsoft Power BI, clearly shows the relationship between products of different brands in the sales history. It can be used to understand which brands are most often purchased by one customer in one transaction. Sometimes it makes sense for a seller to create sets of products from different brands or different product lines.


Fig. 1. Graph of product connectivity
2. Price cascade
As a result of in-depth analysis, it is possible to review not only the product policy, but also the pricing policy of the company. The best tool for its analysis is the construction of a price cascade. This graph shows the difference between the declared price according to the price list and the amount of money actually received by the company as a result of the service provided. Thus, it allows identifying points of profit leakage. These may be, for example, unreasonably high discounts for certain categories of buyers or errors in the process of setting the initial price. We will not describe in detail the advantages of such analysis here, but simply recall the economic constant: a 2% price increase on average leads to a 15% increase in revenue.


Fig. 2. Price cascade model
3. BCG scoring model
To develop a strategy for interaction with individual categories of clients, it is advisable to use the BCG scoring model. It is based on the distribution of clients into 9 segments according to indicators of financial attractiveness and relationship strength. The implementation of the scoring model allows solving the problem of overloading production lines with excessively specific orders to meet demand from clients with limited cooperation potential. This is achieved by assessing the partner from the position of its position in the model structure. Based on the scoring results, it is possible to say exactly what tactics should be chosen in communication with such a client: perhaps it is worth making an additional markup on the services provided to him or even terminating cooperation.