Marketers often have a veritable flood of data at their disposal, which offers the opportunity to implement data-driven marketing. However, in order to provide added value, data must be collected, processed, and analyzed to do insightful reporting. This costs a lot of time, especially when working manually.
According to the PHD and WARC surveying 1,721 global senior brand marketers, the respondents spend most of their working time on reporting (88% of the surveyed), followed by planning (83%), and marketing investments analysis (74%) - creative thinking being lower on the list. Comparing these results to a survey performed by the same team over ten years ago, the time spent tracking performance, creating competitive analyses, and producing audience insights has increased by 57% in the last decade. Once the AI technologies penetrated the market, the hours spent on setting up marketing campaigns decreased, in contrast to the hours required for reporting tasks.
Tasks marketers spend their time on
Plenty of companies are investing a great amount of money in visualization solutions like Tableau, PowerBI, Google DataStudio, and Adobe Workspace, but what is the end result? Plenty of specific dashboards require both time and technical expertise to be maintained and lots of manual work to integrate the wishes, resulting in hours spent on sending spreadsheets back and forth internally from one department to another to gather all the data.
"Agencies should already have data and analytics infrastructure in place, as well as talent with niche analytical skills, to be able to keep up with the ever-changing marketing environment."Mark Holden
Worldwide CSO PHD Media
Conclusion: the client receives a “new” solution, adjusted to its needs, which is being positioned as an upgrade with automation but in fact is just another PowerPoint presentation wrapped in gift paper.
But how can data analytics and visualization really help marketers make their working day more efficient and allow them to channel more of their energy toward creative tasks?
The answer to this question is fairly obvious: by gathering the ever-increasing requirements of multiple clients/departments/offices, checking their compatibility with the available dataflows and analytics, separating the core necessities from that “little bit extra” and creating a “one-size-fits-all” dashboard that is scalable and can be rolled out across all the recipients, covering most of their expectations and proving its value when personalization requests start floating in. But the work doesn't stop at this point: to ensure further viability of the solution, market trends and necessities should be further explored to create room for evolution and improvement.
Project communication is a two-way process, implying that both parties, the service provider (in-house or externally) and the recipients, are participating in it and the needs of both have to be met. Failed or intransparent communication is many times the reason why the client underestimates the value of standard reports or loses faith in the solution, although it is capable of covering his needs. Sometimes a quick demonstration of what the solution can do is worth more than a presentation of fifty pages.
What are the actual benefits of standardized reports for a marketer?
Managing multiple clients/products/countries etc. requires much concentration and consistency, the more sophisticated and complex the reports for each of them are, the harder it is to keep track of the differences between them and not overlook some essential details.
A standard report would only require accuracy checking instead of specifics fishing, leading to reduced response times and standardized reporting tasks.
Having a few standard dataflows which are well maintained and rigorously monitored would increase the data quality on the provider’s side due to the catalyzation of the technical and human resources across fewer data sources and delivering high-quality data reports without additional costs caused by the usual extra workload characteristic of non-standard solutions.
Providing a standard solution, exactly like it was presented, would frame expectations to what is actually going to be delivered, excluding miscommunication and ambiguity, helping both the client and the provider to start their relationship from a certain level of trust instead of frustration, building up an even better connection in the course of the collaboration.
If a standard solution is manifesting signs of mischievous data, the provider would have more resources to be directed toward finding a solution and in-depth knowledge of the workflow, which will help solve problems faster, thus benefiting both parties.
A standard solution would not be differentiated among clients in terms of functionality, enabling better transparency over costs for current and potential clients. In this case, opting for a certain provider would not be based on the most attractive price but rather on more valuable factors like reputation, client service, system compatibility, etc.