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Engineering a system to capture change and power Customer Science

Written by
Mark Zou
Published on
February 26, 2024

Customer Science is quickly emerging as a new business discipline for pharma companies to innovate their commercial strategies, combining data science, behavioral science, and AI to gain a deep understanding of HCP journey and drive engagement.

Over our past two blogs, Helen Kontozopoulos, ODAIA co-founder, discussed Customer Science being at the center of ODAIA’s founding and current work around customer journeys. And Peter Harbin, VP of industry solutions, looked at the role of AI in propelling Customer Science forward.

In our next two articles, we’ll dive deeper into Customer Science from a product development perspective. To start, let’s go back to ODAIA’s founding again, this time through the lens of engineering and the challenge we set out to solve with MAPTUAL.

ODAIA - Customer Science Webinar - The New Science Behind Meaningful HCP Engagements

AI, what is it good for? Absolutely everything.

When we started ODAIA, we spent a lot of time asking customers about their need for AI and the problems it could help them solve. Data was core to everything. Customers wanted their data to either help them do something better or replace a current workflow entirely. 

The industry’s AI needs fell into two primary categories: 

(1) find insights to interpret, or 

(2) be given the insights to act. 

We referred to this as “fishing vs. being given the fish.” These needs are still true today and influence our approach to solving customers’ most pressing commercial challenges with ODAIA’s solutions.

Fishing: finding insights with dashboards and graphs

On one end of the spectrum, pharma customers simply want to make sense of lots of different data. Put their data in a dashboard, represent it with a bunch of graphs, and give it to their sales reps to use. We call this a discovery workflow – sales reps spending time discovering things for themselves (finding the right physicians) and then interpreting what to do (actions to take with HCPs).

Life Sciences Industry AI Needs, leading to Customer Science

The challenge: it’s hard to make sense of dashboards and graphs. They can be confusing and require sales reps to do the fishing and find their own insights. The insights aren’t intuitive or plain enough to see with a graph. Dashboards look great, but they don’t provide the necessary context for a user to trust the insights. It’s just a bunch of data with no story. So, more times than not, dashboards sit on screens and sales reps don’t use them.

And even if sales reps are empowered to fish for themselves, a person’s ability to mentally juggle all the datasets and potential actions to take is extremely difficult. Consider a rep having to account for specific territory dynamics, appropriately allocate time to nurture the right HCPs with future high-prescribing potential, attend events, and much more - all this becomes virtually impossible to do, much less do well.

Sometimes, a fish is a needle in a haystack. Requiring a sales rep to fish for insights on dashboards and juggle all their other responsibilities is asking a lot.

Fish: providing the insights to act upon

On the other end of the spectrum is the ability to be forward-looking. This need isn’t specific to just life sciences. Organizations across every industry are attempting to turn a sea of data into insights and actions. There is a general trend toward using technology and AI to identify trends and potential steps to take. Microsoft is a good example, with the company embedding Copilot in Excel to help users explore data, find correlations, and drive different outcomes.

Customer Science is the application of this idea in life sciences. When you have lots of data and so many different HCP and patient considerations, looking ahead is critical. Commercial organizations want to serve up predictive insights based on all their data, so sales, marketing, and medical teams know what to do next.

Sales teams, especially, don’t want to fish anymore. They want insights hand-delivered to execute. Just give them the fish. In other words, provide the next best action with HCPs. Tell sales reps which doctors to contact, when to drop a sample, and what message to deliver at the right time. And enable sales managers to better coach their reps and determine the right engagement plan.

Next best action without context falls short

Companies typically want their next best actions in CRM, which is a great delivery system to aggregate and surface insights. But CRM isn’t truly data-driven because the system is mostly at the mercy of users inputting data. Getting data in CRM is highly manual, not automated. The system is designed to help sales reps execute, but CRM doesn’t leverage all the data available to commercial organizations. And as we know, generating insights is only as good as the data.

While the next best action in CRM is an attempt to give sales reps fish, insights are still missing context. Sales reps are given such granular, prescriptive actions (call now, email two hours later, then call again tomorrow), that they don’t trust the insights and ignore the actions because there’s no data to explain “why.” Without context, they think the insights are irrelevant or, worse, inaccurate.

So, our question became, how can we help customers fish directly for insights and automate the delivery of fish, or next best actions, so all sales reps need to do is execute?

We call this Customer Science.

Customer Science finally answers “why”

Data is the fuel behind AI, and AI, along with data science and behavioral science, powers Customer Science. AI finds the insights to determine which HCPs are critical. Most importantly, AI makes reason of HCP behaviors and trends, what’s happening and why, to predict what will happen next with HCPs and their patients. Customer Science does the fishing and delivers the fish directly to commercial organizations.

Commercial organizations typically patchwork a range of tools together to find fish and deliver fish. Consequently, the end-to-end engagement process, from targeting and pre-calling planning to driving the next best action with HCPs, remains broken and inefficient in delivering insights.

ODAIA - designed and engineered for adoption - our product is an end-to-end offering because we have built it from the ground up to drive adoption and ultimately lift.

With Customer Science, biopharma companies can streamline the entire HCP engagement process. We bring everything together with MAPTUAL, specializing in pharma data, user personas, business problems, and stakeholders, from commercial leaders to sales reps. 

Our vision is to reimagine how pharma commercial teams work together, through data. We want to help sales management, marketers, MSLs, and the entire commercial organization stop fishing and give them the fish to act, all in one off-the-shelf, packaged cloud solution.

Before MAPTUAL, we realized that the next best action is typically given to consulting companies as a last mile problem, or a final stage in the HCP engagement process to give sales and marketing insights to drive their interactions with physicians. MAPTUAL aims to be so intuitive, it finds the insights and tells commercials teams what to do next in a single, real-time workflow.

Moving beyond last mile AI consulting projects

The typical pharma commercial organization has different groups combing through a variety of data. Syndicated market data provides targeting segmentation. Sales operations determines the right frequency and cadence to see HCPs based on that segmentation. And marketing defines the messages to deliver in which situations. 

Not only are there multiple groups, but multiple products collecting and analyzing all a commercial organization’s information. Even after all this work is done, all this historical data is handed over to an outside consultant in a last mile effort to run more software, perhaps AI, to derive insights.

This approach works in a world where the customer journey stays static, and data never changes. But herein lies the challenge with last mile AI consulting projects. By the time a final analysis is done three to six months later, the original data is already outdated. If data is outdated from the start, the entire customer journey goes off course. And, ultimately, insights are no longer valid, and sales teams get the wrong next best action to execute.

Customer Science accounts for all steps before the last mile, starting at the very beginning of the customer journey. To do this well, a sequence of questions is answered accurately from the start. As new data comes in, insights are regularly enhanced for “who and when” along the way. Insights stay timely and relevant because data is constantly fed into a feedback loop and continually optimized. 

MAPTUAL is a system to capture change

We believe the biggest value we can provide pharma users and business stakeholders is to show them what’s changing in real-time so they can act on it. MAPTUAL is an integrated system of engineering, AI, and design solutions that find the insights and hidden stories within multiple datasets, backed by relevant data evidence, with the entire process fully automated. MAPTUAL finds the needles in the haystack, enabling Customer Science in pharma commercial organizations.

In other words, MAPTUAL finally answers the “why” and does it in real-time to capture change. Next best action without real-time is only the third or fourth best action.

“Other solutions on the market have machine learning. They have insights. They may even have scoring. But they lack explainability. They have no recommendations about the “why”. In order to get your salesforce bought into a new solution, you need to provide them with why that customer is important.”

- Head of HCP Experience at a Top 10 pharma company

To solve this from a product perspective, it’s not just about UX design, but also engineering from the start. Data science, behavioral science, and AI are ingredients. But MAPTUAL is a system of models, algorithms, pipelines, infrastructures, architectures, large datasets, and enhanced data features – all engineered into a single cloud solution.

It’s like building a Ferrari. Lots of companies build engines. We build the engine, but we also make the transmission, brake system, airbags, and everything else. We’re building the entire car. You can’t do Customer Science with just a single engine. You need the entire car. And this is why we believe pharma companies are in desperate need of an innovative product company with experience building complex systems to help.

In our next blog, we’ll take a deeper look at next best action, the limitations of rules-driven insights, engineering MAPTUAL with a focus on being truly data-driven, scalable, and useable, and a future free of rules.

Until then, you can hear more about Customer Science at our upcoming webinar, The New Science Behind Meaningful HCP Engagements. Be sure to register here.

Mark Zou

Chief Product Officer

Experienced Software Engineering and Product professional. With a Master's degree in Engineering Product Design, Mark specializes in new product development. Mark has worked for Morega (exit to AT&T), RBC and Tribalscale.

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