First mistakes and successes in the Bashfully MVP process
This is part of a series about my side project Bashfully, which aims to give graduates and other new entrants to careers a seasoned professional level way of expressing themselves through the super power of story telling. Following the core principles of being discoverable, personalised and guiding in approach.
Since writing about Public beta and starting the MVP process I have gained more insights about our Bashfully launch. These are around what we have got right vs wrong.
Successes
The Twitter campaign had a segment list, budget, and set of content we could re-run. This allowed us to see that the Twitter engagements this time weren't being matched with similar conversion rates.
Exactly what we got wrong is what are trying to prove. But one thing is that we inadvertently changed a variable on the landing page.
This took the logo away from the landing page, moving it to a reusable sign in screen. This also made the registration button a generic button as below
Another theory is that the copy around the registration button made a difference. Luckily this is easier to do a simple A/B test around. So we'll tackle that first!
Whatever the cause another thing we did right was "releasing" early. First by having the equivalent of a download page to gauge interest in the idea. The second was then release a functioning version of the profile. This had about a third of the intended features. The main aim here was to gauge interest and to get feedback on the remaining features.
Overall, I'm please with the progress so far. Trying to adopt an experimentation and data-informed mindset is paying off already. We are able to treat any solutions to problems we find as hypothesis and test them. In the next phase we are also going to step up some qualitative user research.
Since writing about Public beta and starting the MVP process I have gained more insights about our Bashfully launch. These are around what we have got right vs wrong.
Successes
- Having a pre-release landing page
- Having a baseline twitter campaign
- Using the above to get a baseline conversion ratio
The Twitter campaign had a segment list, budget, and set of content we could re-run. This allowed us to see that the Twitter engagements this time weren't being matched with similar conversion rates.
Exactly what we got wrong is what are trying to prove. But one thing is that we inadvertently changed a variable on the landing page.
Another theory is that the copy around the registration button made a difference. Luckily this is easier to do a simple A/B test around. So we'll tackle that first!
Whatever the cause another thing we did right was "releasing" early. First by having the equivalent of a download page to gauge interest in the idea. The second was then release a functioning version of the profile. This had about a third of the intended features. The main aim here was to gauge interest and to get feedback on the remaining features.
Overall, I'm please with the progress so far. Trying to adopt an experimentation and data-informed mindset is paying off already. We are able to treat any solutions to problems we find as hypothesis and test them. In the next phase we are also going to step up some qualitative user research.
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