We set the course for the direction that we want our product to take by investing in Key Business Outcomes and deriving impact scores. Our Impact Driven Product may still have some assumptions we made about why our product will succeed. However, we’re still making these assumptions in the blind. Even when we have ample data from customer interviews and our study of the market and have a good hold on what the market needs, the real data only comes if the market actually adopts our product in the way that we assumed it would. How our users perceive the value of our product may or may not match our intended value. We need to look out for the evidence that points us to anything that challenges our assumptions about the product. However, if we look only for confirmation of our assumptions, the chances are that we will always find it. Confirmation bias will ensure that we continue to read only the signals that will reinforce our existing beliefs.
This is a problem because it will take us much longer to realize that our product is a failure, and we may have lost precious time and opportunity to course correct. It also means that we may lose out on finding new purposes that customers might be using our product for, in ways that we didn’t anticipate. We may lose an opportunity to discover customers who use our product for problems that we didn’t intend to solve. In the previous chapter, we read about how the urban migrant settlers used the solar power devices for powering their TVs, rather than using them for basic lighting needs. This is a good case in point about customers using our solutions in ways that we didn’t intend.
So, in essence, perceived value – proposed value = business opportunity.
The proposed value is the value that a business attaches to the impact their product creates for the target customer. The perceived value is the value that the customer attaches to the product. In both cases, the value is a combination of how well the product meets customers’ needs and solves their problems, and how satisfying the product experience is.
The difference between these two values can indicate the business opportunity/potential. When the business values its product more than the consumers does, it stands to lose out to its competition because customer retention and loyalty drops. However, when consumers value a product more than the business or use the product in ways not anticipated, it opens up opportunities to increase revenue and market share, and also for new business models/products.
A case in point is how the company CommonFloor pivoted its business model. CommonFloor launched as an apartment community management solution in India. The initial intent was to create a forum for apartment residents to be able to communicate, share, and interact with each other. However, when the founding team analyzed the nature of the posts and interactions between community members on forums of all the apartments they had on-boarded, they discovered something unique and interesting. They observed that many of the postings on the open forum were around the buying/selling or renting properties.
The founders realized the potential that their platform held. They had uncovered a new opportunity and an unmet need of their customers. People didn’t have an easy way to post rental listings online. This realization was what led to the re-imagination of the platform as a real estate listing portal.
Quoting Lalit Mangal, the then CTO and cofounder of CommonFloor (which is now acquired by Quikr) from a published article: “In the initial years, we noticed a lot of home owners had started using our platform to post listings. We realized that it would add much more value to the owners if we opened this information to people outside the gated communities. We started project listing on our site. When we noticed that the traffic on our website increased, we started verifying the listed properties. Soon, we were recognized as the best place for genuine listings and started seeing a lot of traction from those looking to buy/sell or rent a house.“ (http://emavericks.in/wp-content/uploads/2015/11/eMavericks-Insight-Volume-1-Issue-3.pdf.)
Success metrics, that we defined as part of our features, are a great place to look for indicators that tell us how close or far we are from our success goals. The number of leads, customer retention rates, new customers gained, profits, revenue, and so on are tangible measurable matrices. However, taking the numbers at face value and not understanding the rationale behind those numbers is not a great move.
Let’s assume that we had a success goal of gaining 500 new customers in the 3 months after our launch. What happens when we don’t meet that goal? The response that most of us have when we see numbers that don’t meet our success criteria is to blame the first, most convenient event. We might say, “The website outage might have been the reason. The emailers didn’t go on time. We don’t have a dedicated support team.” This is attribution bias: we surmise that a one-off event caused our failure or that we didn’t try hard enough. Yet, with an invigorating pep-talk, and a grand vision laid out, we could all do better this time. We re-establish our goals and set off on the same mission without changing a thing in our product. Our conviction that our product is great, and the failure is only due to some external factor or bad luck is sure to set us back on finding the right reasons that caused our product to fail. Openness to feedback, a willingness to go beyond looking at numbers at face value, and uncovering the customer context that could influence the success/failure of our product, is essential for product management.
Even among the customer segment that purchased our product, we need to explore how well they use our product. Are there parts of our product that are used more often than the others? How often do our customers seek help from us? How many customer complaints do we receive? What nature of complaints do we receive? Is there a certain type of user or a certain demography that uses our product more frequently than others?
Product managers must continue to keep alive the idea of exploratory feedback loops. We need to ask the questions that we didn’t anticipate before building the product. We need the ability to look for clues and patterns in the existing metrics we have. We need to find ways to discover the silent/indifferent customers and engage with them. We also can assess what new functionality to introduce in our product. Do customers feel a that lack of functionality is limiting their use of the product? Is there a new feature that customers are willing to pay more for? Each feature should go through a problem/solution fit validation.
Some of these actions can be carried out by just playing around with product pricing. We can assess how much more customers are willing to pay for a new feature. We could propose different plans and feature bundles to different sets of customers and validate which feature bundle works well. The most fundamental questions are: if we increase the price of the product by introducing this new feature, how will it affect our acquisitions and retentions? If we remove this product feature without decreasing the price, are we losing customers?