Kicking off a data tracking discovery the right way
In this blog post, we help you to clarify a few key points when doing a data discovery.
It is fundamental for a data team to not be lagging behind during the development process. Build, measure, learn - our motto in agile is outrun in the race to the newest feature instead of incremental improvements based on a data driven model.
Very often, the data team at Wiredcraft acts as a part of the product discussion as a whole: we’re delivering a product to answer a business question and as such we must validate the efficiency of our assumptions. The temptation is high to report the KPIs identified in the initial sprint and simply limit the implementation to that.
However, internal digital teams (your clients) are now requested to provide data for the whole organization: revenue, operations, e-commerce, leadership, etc. To stay on top of things, you will need to understand not only what to track, but also who will request data and how to report KPIs and insights.
Ignore one of the departments and you will have to run to provide a dashboard, at the last minute, on the night of your brand new deployment. Anticipate these needs and you will be able to mitigate these risks. Ignore any of the what, who, how and you’ll discredit how data contributes to your client’s success.
To turn this around, we standardized our discovery process to evaluate data needs when kicking off a project.
This template covers what we think are the most fundamental points while doing a data discovery for you to prepare your implementation.
Who owns what?
The first objective is to understand the decision process for all-things-data: the key stakeholders who will validate the objectives of your data measurement plan, confirm the insights, and advocate for implementation of the next steps.
Is there an higher level executive who owns and sponsors Web Analytics? What role does he/she play in prioritization, problem resolution, or promotion of analytics?
Where does web analytics stand within the organization? Is it an independent function or does it sit inside another department (Business Intelligence, Marketing, IT)?
What are the core acquisition channels? Are they managed centrally by the marketing team? How much relies on third party suppliers?
Is there an omni-channel measurement strategy?
The client’s level of familiarity with data driven strategies will determine how much education will be necessary for your team to be part of the product design and which dashboards will be expected from you. From our experience with clients who have little familiarity with data, it’s better to go slowly, iteratively while showing quick wins from the very beginning. Your goal here is to understand how deep data culture is rooted within your client.
Does the organization have an omni-channel strategy in place with clearly defined business objectives? If so, how is this strategy communicated throughout the organization (dashboard, reporting)?
Is there an online measurement strategy for measuring online business performance vs. business objectives? Is there a common set of KPIs behind that the different teams are aware of?
Who is the audience for the dashboards and weekly/monthly reporting? What reports are most valued by the Executive team within the organization?
Where does data stand in the product lifecycle?
Finally, you will want to understand how data helps product design and how much time should be planned to run an initial data audit.
To which extent do you think your Analytics data is the foundation for online initiatives?
Which department within the organization typically drives product improvements, features and functionality? How data driven do you think these changes are, on a scale of 1 to 10?
When implementing new features, at what point is the web analytics looped in? Is there a defined process in place for when to consider web analytics? Can you outline the process?
Is there a QA/validation process in place to ensure data integrity and that every release is evaluated regarding business requirements?
Does the organization have Corporate Standards for Web Analytics in place? This would include a shared set of KPIs and reports, approved segments, standards for data collection, data dictionary, standard solution design etc.
Answer these questions and you’ll have a much better understanding of your client’s familiarity with data, stakeholders to pay particular attention to, and direction to take with your initial implementation.
Wiredcraft has engineered large scale digital products and omnichannel setup for the likes of Starbucks, Nike or Burberry for offline to online and omnichannel setup.