Market access teams spend a lot of time preparing for payer meetings, but they rarely know how well those meetings went. To answer that need, MMIT’s Message Monitor has been capturing unaided, immediate payer feedback on pharma meetings for the past 15 years, providing clients with qualitative and quantitative data.
Now, with the platform’s new self-service interface and Ella AI querying tool, teams can explore the entire Message Monitor archive directly, asking the kinds of strategy questions that used to require weeks of analyst work. We sat down with Nick Waldron, an associate consultant in Advisory Services at MMIT, to talk through how teams are actually using this data.
Let’s start with how teams determine which value props to share with payers. How do they assess if that messaging is effective?
Before launch, a market access team will do its research to understand what’s most important to payers in that space, whether that’s a drug’s safety profile, a new MoA — whatever it may be. They’ll have a good handle on how payers are already managing current treatments, and from that, they’ll figure out their best differentiators. Some pharma companies conduct a mock P&T committee meeting to troubleshoot how those value props land with payers, but some go in blind.
That’s actually a huge problem for manufacturers, because once they’re giving presentations to payers, their account team has no feedback to work with. When they walk out of a meeting, they have no idea if their story landed, or if the payer is sitting there wishing they’d presented some other kind of data. Maybe they didn’t prioritize their points correctly, or they assumed payers would be more excited about their differentiators than they really are. It’s very difficult to guess how well you did and what the payer plans to do next after hearing your case.
So how long does it typically take a market access team to realize their messaging isn’t landing?
That’s a good question. The honest answer is probably months, and even then, you’re usually inferring it from outcomes rather than hearing it directly. You start to see a lack of coverage, or restrictive coverage coming through, unfavorable PA criteria showing up, and you might realize that something’s not landing the way it should. Occasionally, in a meeting, a payer might hint what they think about a competitor’s product relative to yours, but you can’t count on that.
Before they come to us, most clients don’t know how their story’s landing or what their competitors are saying. They don’t know whether to lean harder on their dosing schedule or outcomes data, or how to counter competitive messaging that payers are already responding to. They’re operating in a vacuum.
Tell me about Message Monitor. How does it fill that gap?
Message Monitor captures unaided recall immediately after these meetings, so market access teams can get that payer feedback they were missing. It uses payer panelist surveys, which means that someone on the payer side who was in that meeting sits down within 48 hours and shares what they actually took away from it, what they thought about the account manager or MSL’s presentation, and what they’re likely to do as a result. In addition to all the qualitative comments Message Monitor collects, we also provide quantitative ratings on delivery, credibility, and relevancy, because the payer also rates the pharma company in each of those areas from 1 to 7.
MMIT is the only organization that can provide payer intelligence with this kind of historical depth. We have more than 15 years of messages across 1,000+ therapeutic areas. You can’t replicate that with a one-off research project.
What does ‘unaided recall’ mean in this context—is that important?
Yes. In a market research survey, you typically give the respondent some sample content to read first, a stimulus, and then ask questions. Having those prompts steers them, even when you’re trying to be neutral. There’s no leading the witness with Message Monitor. The payer comes in and just reports what they remember, what they thought, and what they’re going to do. There’s no priming or framing from us.
And the 48-hour window compounds that. If a payer is asked to recall a meeting from six weeks ago, they are unlikely to remember important specifics. Getting that feedback while the meeting is fresh means you’re getting the real thing.
Unaided recall can uncover things you would never know otherwise. For example, clients are sometimes surprised to find out that payers are attributing their differentiator to a competitor. The payer walked out of that meeting, in a day of many meetings, and associated that data point with the wrong brand.
Let’s talk about the 15-year data archive. Why is that historical data so useful?
Trend identification is much richer when you have so much data to draw upon. Obviously, you’re not going to go back and analyze what payers thought about a drug from a decade ago, because that’s not relevant. But having the past couple of years of data lets you understand how payer priorities have shifted in a particular indication. As new therapies have come to market, what have payers started asking for?
And it’s not just about category trends. One of the things I keep coming back to is the account-specific angle. You can go into Message Monitor and say, “I have a meeting with CVS next week. What messages have resonated with CVS in the past year? What are they always pushing back on? What data have they specifically asked for that manufacturers didn’t bring? You can walk into that meeting prepared in a way that wasn’t possible before.
Payers can vary significantly in what they care about, by the way. We’ll see one national plan consistently asking for comparative studies, and another saying, actually, what we really want is long-term safety data. One of my clients is in the denosumab biosimilar space, and we’ve seen messages from Centene making it clear that as more biosimilars come to market, they only plan to prefer three of them; every other product will have to step through those preferred options first. If you’re going into a Centene meeting and you don’t know that, you’re behind before you even start.
So having the ability to query this data with AI is not just about getting the same information faster. It’s about asking questions that you couldn’t even ask before.
Right, exactly. The platform isn’t replacing real-time alerts; those still exist. When a new message comes in, clients get an email notification and a direct link. The difference is everything’s under one roof now, and you’re not sifting through months of PowerPoint deliverables trying to piece together a pattern…which you probably wouldn’t have had time to do in the first place.
Ella is essentially a senior analyst who reads everything and never forgets any of it. You can bounce any question off her and she’ll synthesize across all of that data to get you right to the answer. And she’ll tell you which specific meetings she’s drawing from, which is really important, because clients can always drill down and verify, get a little more nuance.
Can you walk us through an example of how a market team would use Ella AI within Message Monitor?
Sure. Let me give you a concrete one. Say you’re in the cholesterol space and you see a message come in: a competitor just met with a major PBM about a newly launched oral therapy in your class. You can click into the details and see exactly what the MSL presented, what the payer recalled from the meeting, and their reaction. In this case, the payer was generally positive about the idea of having an oral option that could potentially address adherence issues, but they flagged a significant gap: there were no long-term cardiovascular outcomes data. The company had launched without conducting outcomes studies, essentially resting on the class’s established track record. The payer response was pretty direct: the data we really want isn’t available yet, and that’s an issue.
Now you’ve read one message. Is that one payer’s reaction, or is it a pattern? That’s where Ella comes in. You ask: “What’s the overall payer sentiment on this new oral therapy in our class?” She responds immediately with an executive summary, and everything she cites links back to specific meetings you can click into.
In this case, the executive summary confirmed that the oral route is genuinely differentiated, and the adherence argument is resonating because a pill is easier for patients than an injection. But payer enthusiasm is being dampened by the outcomes gap. Lots of payers want to see cardiovascular outcomes data before they move on coverage. On top of that, there’s skepticism around the drug’s fasting requirement, because the fact that you have to take the pill on an empty stomach undercuts the adherence story a little bit.
At that point, Ella would provide the logical next steps—what does that team actually need to do? In this example, the client was advised to bridge the outcomes gap and sharpen their economic story. A couple of payers were specifically asking for a budget impact model, and at least one large plan was asking about comparative net pricing against a heavily rebated competitor.
What are some other types of trend questions that Ella handles well?
Overarching category trends are a big one. You can ask something like, “In the past six months, what are the key trends in how payers are responding to messages in atopic dermatitis?” And Ella will give you the executive summary, call out specific brands and payers, and surface the themes running across all of it. It’s the kind of synthesis work that used to require someone to sit down and read through hundreds of individual messages.
I’ve been watching atopic derm closely lately, actually. We’ve seen a lot of messages coming in about a couple of biologics recently approved for extended dosing, every eight weeks instead of every four. That extended schedule is resonating hard with payers because it drives cost savings, and competitors are going to have to respond. A topical treatment can’t make that same argument, so they’ll need a different angle to demonstrate comparable value. Message Monitor is where you see competitive pressure like this developing in real time, before it shows up in coverage decisions.
Which members of a market access team use this intelligence on a daily basis?
When we have readouts with clients, the people in the room are your payer marketers, your account managers, brand strategy leads, and the broader market access team. If a client has a competitive insights role, that person would be there too.
Account managers are probably the ones who get the most tactical value from the platform. They’re the ones going into meetings with specific payers and needing that account-level intelligence, like what does this plan consistently ask for. That’s extremely actionable prep material.
The broader strategy team is looking more at category-wide trends and using that to inform messaging strategy over a longer horizon. Pharma teams that consistently incorporate payer feedback are running an iterative loop, refining what they present based on what payers actually want and respond to. Over time, that translates into better coverage and better access for patients.
Ready to see how your value story compares to your competitors? Learn more about Message Monitor with Ella AI.
