By Bridget Kerry, Solutions Analyst at Clevertar

As a consumer, you likely have a favourite product that you love and rely on. Perhaps it’s your go-to haircare item. Or maybe it’s that productivity app you use religiously. Whatever it may be, chances are, the reason you love it so much is because it helps solve a problem for you. This is the key to successful products – they need to address a need or pain point that users have. To identify these pain points correctly, you need to build a product based on the foundation of user research. Clevertar has done just that by undertaking extensive user research in order to leverage the exciting advancements of large language models (LLMs) and explore opportunities within ecommerce.

User research will inform the development of an initial minimal viable product (MVP) and guide the product roadmap for future iterations. Focusing on impactful features, and gathering feedback with each iteration, provides maximum value for users.

When Clevertar set out to build a product using our expertise in conversational AI, we knew it was crucial to find product-market fit and build a product that will satisfy a strong market demand. As a business, it was important that we didn’t form a biased view on our product and the problems it would solve as it might not necessarily align with those of our target market.

While you may think that you might know what problems your product will solve, you must remember that you are not your own target market.

Therefore we embarked on desktop, competitive research and early product testing to better understand our potential users. We tentatively identified ecommerce as an attractive target market, but knew we needed to listen to potential users to validate our assumptions.

To gather this valuable data, we conducted qualitative user research in the form of interviews with professionals in the e-commerce industry. We crafted a list of open-ended questions that covered various aspects of e-commerce, including challenges related to personalisation, upselling, abandoned carts, reviews, and customer service. We also asked about any barriers or preconceived ideas about adopting AI. We discovered it was important for us to phrase the questions neutrally to avoid confirmation bias and to seek opinions from external sources rather than personal contacts to minimise preconceived notions.

Through these interviews, we received valuable feedback on our initial product ideas.

We confirmed that:

• • Quick responses to customer enquiries are vital in closing sales.
  • Team members are often overwhelmed with questions so response time is a limiting factor.
  • Social proof is important to businesses as it helps to build trust with customers and influences conversion rates.
  • It’s important that technology plugins don’t get in the way of the user experience and detract from a potential sale. Solutions need to be designed in a way that improves the customer experience not make it harder for merchants to sell their products.

On the other hand, we also discovered some surprising insights from our interview data.

We realised that:

• • Cart abandonment and upselling were not seen as top priorities for retailers, as many already had strategies in place to address these issues.
  • Businesses focused more on personalisation in their marketing efforts rather than on their websites, and further personalisation was not considered a high priority.

The results of these interviews have helped to shape our MVP plans by focusing our priorities on the most essential features for merchants. We have then been able to construct a development roadmap that incorporates other desired features and helps us to plan out what will hopefully be a successful and appealing product.

Overall, our qualitative user research was instrumental in validating and invalidating our different hypotheses and provided valuable insights into the pain points and needs of our target market. Building a successful product requires deep understanding of the problems it will solve for users and this needs to permeate the entire product development process. Based on our research findings, Clevertar is now building an MVP with an ecommerce customer service focus.