Even before developing a dashboard, it is necessary to determine who will use it and what tasks it will solve. Only by knowing what questions the dashboard should answer. Algorithm for successfulit is possible to determine what metrics and parameters need to be collected.
Also at this stage, it is necessary to define formulas for calculation indicators and standardize them. This will help to avoid a situation usa whatsapp data where the sales and marketing departments calculate and interpret ROMI. Algorithm for successful CAC and other similar indicators differently. Until there is an understanding between departments within the customer’s company, no automation of analytics will help improve the result.
Stage 2. Audit of data collection systems
It is important to analyze and improve the statistics collection systems even before starting data collection and developing an analytical dashboard:
- analytics systems (Yandex Metrica or Google Analytics). Statistics should be collected for all pages of the site, all advertising landings and domains. The analytics system should collect data for the entire funnel. Algorithm for successful including intermediate stages of application processing. If we are talking customer data platform: data that creates value about an e-com project, the correct operation of e-commerce is also important.
- call tracking systems. It is necessary to collect data on the volume of calls from the site, mapping services and other sites where your business is presented. It is important to set up dynamic call tracking. Algorithm for successful which will allow you to track the effectiveness of contextual advertising right down to the search query.
- additional communication channels. It is necessary to check how requests to the company’s messengers are tracked, and at the stage of architecture design, provide for the necessary improvements so that none of the communication channels with clients remains untracked.
- CRM. The key element of analytics is determining the source of sales. In order for a business to optimize and scale advertising activities, it is important to track which advertising format and channel brings in a converting and loyal audience, rather than empty applications.
Stage 3. Development of technical specifications
We describe what we expect to receive as part of analytics automation. The TOR should include a description of the metrics involved. Algorithm for successful parameters, formulas for calculation indicators, as well as a description of how data from different systems will be linked. At this stage, we regulate the technologies used and the resources required to support the performance of analytics.
Stage 4. Implementation of the analytics project and technical support
We start collecting data and developing a prototype in accordance with the technical specifications and customer requests. This phone number vietnam may require several iterations of improvements based on feedback from specialists who will ultimately use analytics as a working tool. And it is normal when, during the implementation process, it is necessary to adjust the visualization or supplement the data, the main thing is that this does not contradict the agreements at the previous stages.