Location Analytics: A Behind-the-Scenes Look With Bianca Gherardi, Technical Product Manager

This past summer, we got the opportunity to visit Cuebiq’s Milan office and interview some of our brilliant Italian counterparts, who help keep Cuebiq running day in and day out. Meet Bianca Gherardi, Technical Product Manager for Cuebiq’s Analytics product, and previously a Data Scientist, who has worked with Cuebiq for over a year. Bianca is excited about the breakthroughs we are making in location analytics and is eager to share her experience working at Cuebiq and how she has evolved within the company. What follows is an excerpt from our conversation.

Bianca Product Manager

Can you describe your journey at Cuebiq and how you came to work on Analytics?

I began my experience here with two months of training and learning about data, then moved on to working on Analytics as a Data Scientist. I then changed jobs and moved teams to become a Product Manager. The reasoning behind this was that being a Data Scientist was a job I already knew, and I had new goals I wanted to reach. Being a Product Manager gives me the opportunity to work toward those goals and develop new skills.

How does the job of Product Manager compare to that of Data Scientist?

The Analytics pod is a group of eight or nine people, which is big for a first experience as a Product Manager. However, I do miss working with data — but that’s the only thing that I miss, and I already know how to do that. Before this job I didn’t know how to manage people, but I’m learning how to do it and I really like it.

Do you work with US teams at all, or any other teams?

I work with almost all the teams except Attribution and Architecture, so that means I work with the Data Scientists, with BI, with the platform and Dev Ops. In the US, I work closely with Operations and Marketing. I get the opportunity to travel to the US often to connect with employees in our NYC headquarters, and I’ve also been able to attend some industry conferences to enhance my skills and knowledge.

What was it like working on a product in beta? Are there any challenges you’ve faced with that?

It’s challenging that the product is in beta — this moment is crucial, and we can’t afford to make mistakes. The reality is that in this first phase, mistakes do happen. Every time there’s a bug, we have to solve it very quickly, which is challenging but at the same time very rewarding. Working on Analytics has improved my problem-solving skills and has allowed me to take on new responsibilities, which has been very fun!

What excites you most about the Analytics product?

The potential of a product like this is what excites me most. Within Analytics, there are so many innovative features that are all connected and enable our clients to create a story around the product. For example, if you start with visit data, you can then go more in depth to understand the behavior of your consumers, their demographic and shopping characteristics, and also get a geographical view of their buying habits. This product empowers our clients to better understand the offline consumer journey via real-world insights and activate against those insights to strengthen their business strategies and help measure their marketing activations.

What’s your favorite feature?

Loyalty! I love showing and explaining how the brand loyalty tab within Clara works — this feature enables brands to better understand how loyal consumers are both to their brand and as well as to their competitors. By getting more granular insights, our clients can identify what’s working and which areas they can improve upon. With Analytics, our clients can easily visualize brand loyalty in terms of visits and then quickly activate new tactics, such as competitive conquesting of vulnerable audiences directly within Clara!

What does the future of Analytics look like in the next year?

In the next year we will be adding a feature that will permit clients to customize the product even further to cater to their needs. We are also always working to improve and strengthen the product based on market needs and client feedback. One of the more interesting analyses we’re adding is the path analysis. Only we can provide this, because we have the most accurate and precise location data at scale, allowing us to create a full picture of the offline consumer journey and consumers’ path to purchase.

If you’d like to learn more about Cuebiq’s Analytics product, schedule a meeting with us.

Cuebiq Marketing Team