What is Tvito?
Tvito is a product that helps restaurants make social media images fast for their promotion. It is a product of Petpooja, a B2B SaaS for restaurants for billing and menu management.
When working with restaurants, team identified that in restaurants discretionary spending is high and it is important for restaurants to stay in the limelight and build a brand.
Restaurant owners invest in digital marketing and many promotional products are seasonal, leading to high creation of timely and relevant images.
This led to creation of Tvito product which helps restaurants prepare images faster for their social media posts, menus, social promotion and seasonal promotion, so now Tvito is a library of 1000s of Food images
Soon they got traction and realised that current set of tools are not adequate to manage their data and they need something more, so on a call with VP of Initiatives, Tapan Patel Optiblack introduced them to the solution of managing data.
What problem you faced before you started working with Optiblack?
The core product promise of Tvito is the images that restaurants can create fast
Before started working with Optiblack, Tvito faced following challenges
- Lack of understanding of user behavioural data
- Lack of understanding in asset Utilization
- Exploring avenues of monetization
Tvito realised Google Analytics was not meeting their needs, it lacked the required user interface and solve these problems in efficient manner
Had they not made any change, they would have continued to take decisions on gut feeling instead of backing with data, they would have continued to take decisions without a proper direction and struggled in asset utilisation
What you did to solve that problem?
To address the challenges faced, Optiblack introduced Mixpanel to the Tvito team
Mixpanel is a product analytics tool that provides insight into the behaviour of users
Optiblack gave a business case to Tvito and showed on demo on how they can use Mixpanel to address the challenges of user journey, monetization and asset utilization
Why Optiblack?
Tvito decided to go with Optiblack, this is what Tapan Patel, VP of New Initiatives at Tvito said:
“Embedding an analytics tool without opting for onboarding support became a nightmare for us in an earlier experience. It costed us poor data linking, delayed number crunching, and hence slowed down our journey.
This time we chose Optiblack. Their approach made the execution faster. They offered us effective onboarding support. Following their processes, we could cut down our implementation time and internal learning cycle.”
Another reason of choosing Optiblack was they needed someone who understands product and then develop a strategy instead of just providing tech implementation support as the internal tech team is strong enough to read documentation and implement it.
What actions you did after engagement?
Optiblack helped Tvito develop a strategy on what data they need to collect, they developed a tracking plan and strategy for the data collection and provided support for the implementation. Before the closure of project, Optiblack helped team make use of Mixpanel better by doing a training session for the team to discuss how they can use Mixpanel to cover insights
After Tvito installed Mixpanel, they dived deeper into their data to uncover insights.
Tvito provides promotional graphics and food images, they used the Mixpanel data to identify what is driving paid subscriptions and what is driving engagement.
Tvito started looking at the data to see what actions they can take to improve engagement with the app, they identified the supply and demand gap in a segment of North Indian cuisines through the data and started fulfilling the demand through the appropriate images, this insight was not easily available earlier.
How did it impact business?
Tvito got the correct information on what is leading to paid subscription,
Tvito came to know what are users doing inside app and what they do before purchasing a paid plan,
Tvito also found ways to better target users which increased their message relevancy to 80% of users instead of earlier 20%