Data Capture & Management

Contents

On the back of the previous sections focusing on setting up data structures and ensuring it flows smoothly from the Wavumbuzi Platform into HubSpot, this section serves to ensure that data is managed well, built onto with new data capture opportunities, and used for insights on the user journey.

1. Event RSVP & Attendance Capture

2. Keeping Data Clean

3. Google Analytics & Google Tag Manager

1. Event RSVP & Attendance Capture

One entry point for new data into the HubSpot ecosystem is via import, as discussed in the Pre-Challenge User Data section. However, hosting events, like Teacher Training for instance, creates a challenge: either capture RSVPs and attendance details offline and go through the headache of consolidating, cleaning, and importing that data - all the while trying to match these data to existing records. Alternative, one can orchestrate the whole process and the data capture from within HubSpot.

Doing so in recent times has resulted in a fairly well-defined event protocol, the steps of which are documented below:

1. Decision is made to host X event on Y date

2. RSVP form is set up using the HubSpot forms tool

   • An example of one such form can be viewed here

   • Form should include event details and any relevant session selections. For example, if Teacher Training has two stream options, a HubSpot property ought to be set up and used in the form for the respondent to indicate which stream they are choosing

   • Ensure that in "Form Options" the "Always create contact for new email address" is toggled ON to avoid overwriting existing contact information wrongfully

3. Confirmation of RSVP and event reminder automated communications are set up

   • One email to send upon submission of form to confirm session details and submission receipt

   • An example of one such email can be viewed here

   • This will require a simple automated workflow to trigger the send of the email - example here

4. Active lists are set up for event RSVPs and attendees

   • Active lists are lists that include contacts who match a set criteria and which update the contacts therein as new contacts meet the criteria or as existing contacts cease to meet the criteria

   • An active list is composed to compile all those contacts who RSVP to the event, and all those who attend (fill out attendance form). This is for future reference and for use by the Marketing Team when communicating to these segments

   • An example of an active list of RSVPs to an event

5. Event Attendance form is set up and distributed at the event for attendees to fill out

   • Similar to the RSVP form, but capturing only the contacts' key details. Importantly, this ought to include email address so that these form submissions can be automatically matched to their RSVP submissions

2. Keeping Data Clean

With all the effort that goes into getting data and storing it in a useful place, it is exceptionally important that it is kept clean and free of duplication and error. Failing to do so can severely undermine the success of an iteration of Wavumbuzi.

If care is taken to source data and have it updated via API, then data ought to require minimal secondary attention. However, it is useful to have some checks an balances; one which is ongoing during an iteration and one which is periodic.

During gameplay, the most important data policing is to ensure that no schools end up with duplicate entries on the DB. When this happens, users splinter between the different versions of the school. This causes problems with scoring, leaderboards, and down the line, reporting as well. Historically, the Quality Assurance role has conducted weekly reviews of registered schools in the DB to look for potential duplicates. Where they are found, the Super Admin portal has a merge function which can be used to combine the duplicate schools and their users under a single updated record. The QA then communicates to the CRM Administrator the School ID of the record which has been merged and therefore no longer exists, and the CRM Administrator conducts a merge of the relevant HubSpot records.

The second check and balance for long term data cleanliness is data audits and clean-ups between iterations. Because multi-iteration data is not enabled as of the time of writing, there has never been complete data audit of this kind to ensure cleanliness of contacts and companies in HubSpot, but once multi-iteration data is being handled by the Wavumbuzi system, it will become good practice to audit and clean data after each iteration.

3. Google Analytics & Tag Manager

Wavumbuzi Google Analytics Home

Google Analytics serves a broader purpose in the context of Marketing; please consult this section of the document for more comprehensive Google Analytics content.

Wavumbuzi Google Tag Manager Home

However, Google Tag Manager falls within the realm of Systems. That said, this tooling has only recently been introduced into the Wavumbuzi mix, and as at the end of Rwanda 2021, there has yet to be a fully implemented version of the desired Google Tag Manager tracking. Once this is implemented fully, all user actions from registration through to in-game and in-portal actions such as submissions and reviews will be trackable.

Full context on the existing tracking tags and setup instructions are available in this GTM Integration document.