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The evolution of Pollar
Our team designed Pollar with the philosophy of building a lean startup. We see every concept or prototype as an opportunity to learn more about our users and improve our product.
Initial concept
Pollar started off as an attempt to create desirable online ads.
The initial model, named Adpoll, pays people to engage with online ads disguised as polls.
Adpoll's concept
Moment of pivot
We soon find out that a few dollars is not rewarding enough for people to deviate from their browsing habits and start interacting with ads.
Knowing that increasing the dollar reward is not financially viable, we reframed our enquiry to the following:
The course-changing team meeting.
It felt like an aha! moment.
First iteration
So we refined our idea.
Shoppers who complete polls at the checkout page of e-commerces would get instant dollar off their purchase.
The polls could be used for research or marketing.
Early concept sketch
High fidelity prototype
Moving into a high fidelity prototype.
User testing with online shoppers
All the users were willing to complete the polls upon checkout for the coupon, and wish that it is offered at more online shops.
We tested our prototype with 9 online shoppers, and we received extremely positive responses unanimously. Our test focused on observing their reaction with the offer at checkout and the percentage of user who are willing to complete the polls for the discount.
Defining the business model
We mapped out our business model canvas and realised that the net worth of Pollar highly depends on our e-commerce network. However, our current model is not optimised to serve their interest.
The key resources of Pollar lies in our e-commerce partner network.
Our current revenue stream is based on a 5% service charge. The $5 (HKD) charged per response is fully distributed to our e-commerce partners and respondents. This revenue model reflects our vision for a transparent data collection system that pay respondents for their data. However, it also means that our business would only be profitable when we scale at large.
Our current revenue model is not sustainable at a small scale,
so partner recruitment should be our immediate priority.
User testing with online shop owners
To better understand our customer needs, we talked to 4 online shop owners about Pollar. Here's some of their feedback:
I don't want to install things on my checkout page. Shopify doesn't allow changes on the checkout page too.
Well, if there's a way to provide the discount before the checkout I might consider it.
Maybe shops that are less successful would want to do it?
The benefit seems too petty for my shop considering the extra time I need to put into it.
I would give it a try if you do all the set up for me. And you must never make it a pop-up. I can't have it annoy my customers.
Final Iteration
Based on the comments we got, I redesigned Pollar to be a customer retention chatbot for online shops.
Pollar could encourage shoppers to actually make a purchase since they got some discount.
The format of responding to polls through chat also make the experience more personal and fun.
Refining the revenue model
We diversified our revenue stream with a monthly subscription plan for our e-commerce partners. This plan could attract online shops that want to preform customer research to get on-board.
What I learned
User-centred does not equals to end-user centred. I should balance the needs of all stakeholders involved.
Research, research, research. We have made a lot of assumptions about the needs of researchers and online shop owners. As great as it is to iterate upon feedback, it would save us a tremendous amount of time if we talk to our stakeholders in earlier stages. If I were to do this again, I would invite at least one market researcher and online shop owner to every ideation meeting we had.
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