The importance of customer insight in digital intelligence transformation is no longer up for debate. In the digital intelligence era, moving forward without data is extremely difficult. But not every enterprise has a smooth journey when using data for transformation. Recently, some companies have been discussing why previous attempts at conceptually complete data + content + recommendation solutions did not work well in practice. These were not MeDomino data or platforms, and frontline feedback was quite negative. What was the reason behind this?
01 Lessons Learned
*Based on a true story
A large pharma company decided to introduce external HCP profile data to empower sales. Through a partner, it obtained what seemed to be a very detailed set of HCP profile data and launched a new sales strategy project based on it. The project delivered two parts to the sales team: customer profiles and intelligent recommendations based on those profiles, hoping to help the team engage and serve HCPs in a more targeted way. At the beginning, expectations were high. Then the data and tool went live. After the initial freshness faded, usage dropped rapidly. Several rescue attempts failed, and eventually, after internal reflection and discussion, the company decided to stop the project.
Why? The reason was data completeness.
You may have guessed data quality, but perhaps most people did not expect the problem to be completeness rather than accuracy. In other words, data was missing.
When people look at data, they often care a lot about accuracy. Accuracy is of course very important, and it is relatively easy to check and measure. But in this project, what caused negative sales feedback was actually data completeness. We cannot deny that sales teams know their customers well. Even if they do not know something in the short term, they have the ability and opportunity to obtain or verify it. When external data seen by the sales team differs greatly from their own judgment, especially when it misses things that feel obvious, the sales team may directly stop trusting external data. This can then make the entire business department doubt data-driven decision-making.
Of course, the project lead had a difficult time afterward, because the project's main outcome was a lesson learned.
02 Success Story
This brings us to our client, another pharma company. After three years of cooperation, we can finally share this case with confidence.
Three years ago, this pharma company purchased all of its target HCP data from MeDomino at the time, with monthly updates, and has renewed every year since. As the number of target HCPs increased, the total number of profiles also gradually increased. This year, with the introduction of a new product, it expanded into a new disease area.
What was delivered, and how did it perform?
One background detail is that during these three years, except for this year's new product introduction, the company's products, regions, customer scope, and sales team remained quite stable, without major changes. MeDomino's deliverable was actually relatively simple: each sales rep could directly view the profiles of the customers they were responsible for in WeCom, along with monthly dynamic updates. The mobile page was also designed by MeDomino. When the partnership began three years ago, there were no impressive intelligent recommendations. Even after continuous iteration, the system only added some reminders. There was no assessment requirement for sales reps to use it. Usage was entirely voluntary.
As for usage results, let the numbers speak. Every month, 70% of sales reps proactively open the mobile app to view the latest updates on the customers they are responsible for.
Conclusions and Discussion After Comparing the Two Cases
Data quality is the foundation. The more advanced the application, the higher its requirements for data quality. Within data quality, the most important and hardest thing to judge is data completeness.
In the successful case, many people are curious: why do reps open the updates every month? Simply put, they are looking for visit topics. For more detail, contact us and we can discuss it in person.
- MeDomino's physician database contains public data on four million HCPs nationwide, including Chinese and English literature data, conference data, online consultation data, WeChat official account data, and more. This first step ensures the authenticity of HCP360 profiles.
- Based on HCP360 project experience with dozens of leading pharma and medtech companies, MeDomino has refined an industry-recognized standardized HCP evaluation system. Through multidimensional AI parsing, it helps life sciences companies precisely locate target HCPs, quantitatively understand HCP profiles, and continuously track HCP mindsets.
- Finally, MeDomino turns complex data into easy-to-understand visual graphics, making the information clear at a glance.
In reality, the value of HCP360 profiles goes far beyond sales teams. As enterprises become more digitally intelligent, collaboration among teams also becomes increasingly close.
Some may ask, "After saying all this, can MeDomino's HCP data truly be recognized by the business?" I do not know how to answer that directly. But in our past enterprise-level HCP360 project cases, when the client did not set any KPI requirement, more than 70% of sales reps voluntarily used the tool every month. Perhaps that number is already the answer.
