Our new Brand Health Insights Framework is designed to help brands measure and optimize key metrics like salience, preference, and loyalty. This webinar features a conversation between Mike Patterson, Chief Research Officer, and Glenn Staada, Senior Vice President on the new metrics, and how brand teams can gain deeper, actionable insights to drive meaningful growth.
Read the webinar transcript below:
Paul Donagher:
Good afternoon, everybody. My name is Paul Donagher and I’m responsible for client services here at Radius. Thanks to all of you for your interest and for attending today’s webinar, which will be on best practices around refreshing your brand health program with some new thoughts and ideas that we’ve put together for what I think you’ll find is a very interesting framework. Today’s webinar will be led by two of our senior people here, Mike Patterson, Chief Research Officer, and Glenn Staada, Senior Vice President. As always with our webinars, we have scheduled 45 minutes. If you’d like to please type a question as we’re going along. If you’d like to ask Mike or Glenn, what we’ll do is, the will speak for about 30 minutes, and hopefully we’ll have about 10 minutes at the end. So any questions that you’ve got, I’ll collate those.
I’ll group together any of those are quite similar, but we can have some Q&A at the end of it. So by way of introduction and during today’s webinar, among other things, you’ll certainly come away with an enhanced understanding rather of what motivated us to break the traditional brand health model. How we then take brand health framework and move that through to activation. So activation strategies that’ll help you differentiate in the marketplace. Also some deep insights that will provide a foundation for long-term brand growth. As an introduction to today’s speakers first of all, Glenn is an SVP at Radius and, and is based in Princeton, New Jersey. In addition to leading his own client service team here, Glenn also leads our financial services sector bringing his years of experience to clients in that industry.
Glenn lives in Montgomery Township in New Jersey with his wife Joellen. One of the things that they love to do when they’re traveling around the country and around the world is wherever they’re going in the city that they happen to be in. They love to try and sample local cuisine, which is a real passion for them. Mike Patterson is chief research officer here at Radius. Mike built his own business before merging that into the Radius family a number of years ago. Having previously worked on both the supplier and the client side of the business. Mike loves Texas, loves to play golf when he is not involved in developing some unique advanced analytic techniques for us, including in the world of AI, which has taken up a lot of time just now. With that brief introduction, I will turn it over to Glenn.
Glenn Staada:
Thanks Paul. Thank you everybody for joining us today. Before we get started going over what’s comprised within the brand health framework I’d like for you, Mike, to maybe tell us a little bit about the history and, and how it was developed.
Mike Patterson:
Thanks everyone for joining us. When we developed this framework, what we first did is we assembled a team here at Radius, a core team of experts that had a lot of experience in terms of brand health. We got together, we developed some ideas just in terms of best practices that we had seen, best measures, best approaches, et cetera, to use. We also conducted a very extensive literature review. We looked at textbooks, journal articles and even competitive information. We took all of that information together, compiled it together, and came up with a tentative brand tracking framework. Then what we wanted to do was to test that. We conducted a large-scale U.S.-based survey that covered 57 brands, and that was across six different categories or industries. Once we received the data, we performed a variety of different statistical analyses to test and modify the framework so that we could identify which measures worked best and how those measures interplayed with one another. Then essentially what we ended up with, we think, is a framework that is both extremely actionable as well as very statistically sound and robust.
Glenn Staada:
Mike, what are those key metrics that make the Radius brand health framework useful for firms?
Mike Patterson:
Our framework really takes a holistic view of brand health by looking at how a brand is performing across a continuum of different experiences that a buyer can have with the brand. Starting on the left hand of this chart, you can see we begin by understanding how salient a brand is in a consumer’s mind. Then we move to understanding how the brand is perceived across different dimensions. We then assess the preference for the brand overall as well as in relation to competitive brands. Finally, we look at the strength of connection that audiences might have with a brand.
Glenn Staada:
Mike, I think it could be useful to go into a little bit more detail about the specific components of the framework, as some of these elements I know are not included in some of the legacy trackers that I’m working on with my client base.
Mike Patterson:
We’ll start with the left hand side, with brand salience, which really measures the extent to which brands are thought of easily and often at the right time, the right place, and in the desired or intended ways that a company wants it to. Brand salience really focuses on the availability and recognition heuristics that have been derived from behavioral science. That is namely that brands that come to mind very easily are generally more positively viewed and are also just much more likely to be selected or purchased. You can see on this slide that we list the different measures that we typically include aided awareness, unaided awareness, familiarity, and past purchasing behaviors. We can take those measures in combination to understand the extent to which a brand really distinguishes itself in what otherwise could be a very crowded marketplace. The next dimension that we have really deals with brand performance and includes measures that really hone in on the perception of different functional attributes. This allows us to tease out how a brand performs on these more concrete rational items. As we note here, this taps into System 2 measures which assess how a buyer thinks about brands in terms of cognitive evaluative processing. So Glenn, when we’re talking about these types of attributes, what do you think the best way is in order to capture perceptions of functional attributes?
Glenn Staada:
When we’re able to design a new study from scratch, we tend to prefer association questions where a respondent will tell us across a selection of brands that we want to measure in the study, the extent to which on each dimension, they would associate each of those brands with it. So they could pick as many brands as they want, that they believe are represented by that dimension, or they can pick as few. There’s also none. This really gives us the ability to not stress the respondent in terms of having to evaluate brands that they may not have experience with on attributes across a scale. It’s simply kind of, yes, you associate, or no, you don’t. This data allows us to, over time, we’ve found it to be a very reliable way of looking at leverageable strengths by brand opportunities to improve by brand and also identify white space, those areas where really none of the brands are owning a certain dimension moving past functional attributes. Our approach also includes a clever way and potentially a new way to measure emotional attributes. Mike, do you want to provide a little more detail on that?
Mike Patterson:
We definitely believe that there’s real value in measuring the feelings that consumers may have with a brand. We have a variety of different emotional measures that ask consumers how a brand makes them feel, the imagery that they associate with the brand. Examples that come to my mind are things such as a brand you can trust being an ethical company, you know, it’s a brand that values their customers, things like that. We also have a variety of different personality measures that we often will include in brand tracking surveys. These are designed to assess how consumers perceive a brand across a variety of different dimensions. As the brand can be perceived as being caring or hip and cool or maybe a funny sort of brand. As you see on this slide, we list System 1, which really gets at those decisions that are more subconscious in nature that consumers may not be aware of. We find that using System 1 approaches to measurement in combination or conjunction with emotional measures really will yield some very nice results. Also on this slide, we list System 3, and this is a relatively new framework of measurement that tries to get at more imaginative measures that really have respondents project their feelings and their behaviors into the future that allow us to understand how they view a brand.
The next dimension that we measure is preference, and this is both for the brand that our client brand that we, that we’re focused on as well as competitive brands. Within this construct, what we like to do is assess high level preferences that might include things such as overall appeal, value perceptions, the extent to which a company is seen as innovative and as well as the momentum behind a brand. Is it seen as an up-and-coming brand on the way up, or is it seen as a brand that might be declining in terms of perceptions. Then we also like to understand the strength of consideration. So in this case, we assess the likelihood to consider the brand as well as that of competitors. With these measures, we can come to an understanding of the share of preference that a brand might have. So understand the extent to which a brand stands alone and really distinguishes itself versus it’s just simply one of many in a consumer’s mindset. So the next level that we associate and assess is brand resonance. This is the highest level within our framework, and it is composed of a variety of different measures. On this slide, we show loyalty. We’ll also talk about brand connectivity, but when we assess loyalty, we really focus on that positive word-of-mouth that consumers will provide, as well as trying to understand the extent to which they desire to return to or repurchase with a brand.
Glenn Staada:
Mike, I’ve, I’ve seen cases where many satisfied and seemingly loyal customers don’t always purchase from that brand in the future. How does our framework consider that or take that in? Mike Patterson:
As I mentioned, we also measure brand connectivity, because I think you’re right, Glenn, oftentimes we find that a customer may be loyal, but, but it’s not a strong loyalty necessarily. What we try to understand is, how connected, how strong is the relationship that a consumer or a buyer might have with the brand? So this idea of brand connectivity incorporates several different measures. As we show here, we assess the affection that they might have towards the brand, the passion that they might exhibit, as well as the extent to which they feel connected, say to others that are also using the brand. A good example on this last one is Harley-Davidson who has this large community of very vibrant owners who really love and are passionate about their brand. For each of these, we assess these sub measures using a variety of different questions to really hone in and understand at a, at a very tactical level and strategic level, both how consumers feel about each of these dimensions.
Glenn Staada:
Earlier, Mike you mentioned System 3 measurement, and I suspect that is a new concept to many and, and something that’s a bit differentiating for our model. Could you go into a little more detail on what System 3 is?
Mike Patterson:
As I mentioned, it is a relatively new measure, and it’s also very forward-looking, a forward-looking imaginative measure. It asks respondents to project how they think they would feel in different circumstances. For example, when they’re actually purchasing a product or maybe a service, how do they think they would feel when they’re making that purchase or when they’re using a product? How do they think they would feel? Looking outside of themselves, how do they think others would view them knowing that they’ve purchased a product? Or how would others view them when they see them using the product? These are very projective sorts of measures.
Glenn Staada:
So Mike, I think you’ve done a good job of laying out the components of the model across the spectrum and all of the underlying metrics that we’re asking of the brands within any category. Can you tell us how that all comes together to get an overall assessment of brand health?
Mike Patterson:
Sure. We really believe that there’s a lot of value in summarizing brand health using a single metric. What we’ve done is we’ve tested a variety of different approaches, different ways of using the measures that we’ve talked about in order to construct a composite overall brand health measure. With all of that testing, we’ve identified the measures shown on this slide as, as being the most robust. Those measures are the most reliable. What we’ll do is we’ll take salience preference and loyalty connectivity and combine those into an overall measure of brand health. That allows you to compare how your brand is doing vis-à-vis the competition. But then we’re also able to provide very targeted information about how to make improvements. So let’s say that your brand health score is average that you’re on par with many other brands. Can you look to improve in terms of salience or, or perhaps you’re lagging in terms of preference or loyalty connectedness. Our model and approach allow us to really provide that very diagnostic and detailed information.
So Glenn, I know that you’ve got clients that have programs that include some sort of a brand health score. Can you tell us how they typically work with their brand health scores in order to drive their business forward?
Glenn Staada:
One very useful and actionable way that our clients are working with brand health scores is to model the expected results of improvements across the range of whatever functional, emotional, or underlying indicators we include in the study. Oftentimes one of the deliverables will be a brand health simulator. An example of one is here on the screen, and this is an Excel-based tool that allows the user, the end client, their stakeholders, the ability to conduct what if scenarios to determine how improvement on one or several dimensions might impact those kinds of key outcomes. It could be an overall brand health score, it could be the salience measure, it could be the connectivity measure — whatever dependent variables we build the simulator to. Typically we’ll do that on a custom basis, understanding the wants and wishes of the client. This tool then uses statistical modeled results to understand that interplay and that relationship between the underlying measures and that overall brand health score that we’re managing too.
Mike Patterson:
As we mentioned earlier, we did conduct a self-funded study when we were trying to develop and refine our brand health model. As I mentioned, I study a multitude of different sectors. One of the sectors was finance, where we covered a variety of different brands, which you can see here. Glenn, I know that as Paul alluded to, you’ve got a lot of experience in financial services. I think it would be great if you could walk us through how the results of our brand health framework can be used, focusing specifically on those financial services companies.
Glenn Staada:
Mike, if you want to take it to the next slide we’re blinding the scores here across those brands that Mike just mentioned, just so people don’t get distracted on which bank’s winning, which bank’s losing. We took the several hundred responses that we got within financial services, and we framed it to retail banking. We ran all the measures that we talked about, we did all the modeling that we talked about, and we came up with a brand health score for each of the brands. This is indexed to a hundred, so a hundred essentially is the average brand health score. But what’s neat about this is you can see the array from Brand 1 to Brand 9, and it’s quite a distinction in terms of the differentiation.
What’s nice about this is it gives us the ability to really look at a wide range of outcomes, and not every brand is clustered in the same space. So of course, this then is one measure that a brand can now socialize within their organization, get everybody — the key leaders — to understand the score and they can manage that moving forward. For this example of financial services, this brand health score then leads to the, the next slide where we’ve got the underlying parts of the spectrum, the brand health spectrum that Mike introduced. We can start to diagnose for each brand where there are strengths or weaknesses across salience preference, and then that loyalty connection, higher level of brand strength. You’ll see different situations by brand. It’s not the case that a brand is strong across all of them. For some of them there are over a hundred for all of them, but you’ll see a different situation for the brands. I’ll get into that a little bit with some custom summary examples, but this allows us to, on a case by case basis, really start with the diagnosis on, okay, here’s where your brand health is, if you’re looking to improve, these are the areas to focus.
This is just an example using the functional attributes again when we do this for our clients on a custom basis, we’ve got the functional, we’ve got the emotional attributes, we’re using the various techniques like System 1. For this study we’ve got the functional attributes that we had the respondents associate with each of the brands that they’re aware of. And then we ran a regression model to the overall brand health score, so we could get a prioritization of which functional attributes have the most impact on brand health. In this case, within financial services, it was definitely those customer centric measures the ability to, to reach a live representative. The ability to easily do business, and customer service. So now that we have laid out the primary drivers of a brand’s health, we can then move forward, and I know this is a little bit of an eye chart, but each of these individual plots represent the association scores for each of the brands on each of the attributes.
If we are working for a specific brand, we’re going to look at where they come in right now on each of these attributes, starting with those that are most important and working the way down and looking at where their position relative to peers, looking at the distribution of the line from high score to low score, that tells us a little bit about the diversity of perceptions on that attribute. Then we’ll also, we’re not showing it here, but we’ll look at the percentage that said none, none of the brands that we tested are associated with this dimension. That helps us to start to uncover white space, especially those attributes that tend to be more important, but have fewer associations. Those are meaningful opportunities to own dimensions that will link statistically to brand health. This is just a little example of the analysis that we do, but we definitely have a lot more richness than that, that we would include in, in typical programs.
Mike Patterson:
Glenn, I think it could be helpful if you could talk about some of the story and maybe the opportunity that might be available to some of the brands that we’ve included in this analysis.
Glenn Staada:
Sure. Our hypothetical Brand 2, we know it is a real brand, but we’re masking it. Based on what we’ve seen here, and again, there’s other data that we are using to diagnose how the brands are doing, more than what we had time to show you. We would say to Brand 2 that they’re positioned to win by maintaining one of the healthiest financial services brands in the U.S. Their brand health score was 119, second out of nine, definitely strong. When we start to break down the components to look at where they can drive further we find they are the most salient brand in the market. Definitely very, very well known. But when we look at other measures, we see it’s driven by a large customer base, but preference among the market at large is more muted.
We can tie that to more moderate perceptions of value to those that are not yet working with that bank or brand. Additionally, we are able to look and see that they’re leading most significantly on perceptions related to convenience, easy to use mobile apps, and a great online experience, but they’re only moderately perceived as handling customer data responsibly. For a brand like this, we’d be able to give them some recommendations concerning loyalty programs, really help to drive customers into that loyal connectivity space to attract new customers, personalized offers, multi-product benefits, and potentially a campaign on data integrity. Would be one example. If you go to the next one, Mike, this is Brand 5, and they were right in the middle on brand health. But we would say for them that we’ve seen them establish strong sense in the marketplace, but they’re going to be challenged to achieve meaningful growth until they improve perceptions that will drive trial and deeper customer connection.
What we found is they’re very well known nationally only lagging the three largest brands in terms of awareness and familiarity, but loyalty and connection was merely average, so they are very well known, but loyalty and connection was more similar to the lesser known brands. We also saw that perceptions were more on the weaker side on convenience access to customer service. For this brand, we would potentially recommend products and service improvements, targeted marcom campaigns, better use of tech to show needs without that, needs are met without a wide branch network. That comes from some other analysis we did that we haven’t had time to show here. Finally the third and last example, this is Brand 7. So, the assessment here is this brand punches above its weight due to a best in class customer experience model.
This bank is in a position to grow, should it choose to diversify and expand its traditional target. While the brand overall on brand health comes out seventh out of nine at 90, there is a very strong preference among those that know the brand and use the brand. We also see that Brand 7 is their favorite brand often, and there’s very high scores for customer service and value relative to cost. So we see this as a situation where that salience numbered 56, that really is the biggest thing holding this brand back, go out there, you’re positioned to grow if you want to make a play. So we just picked these three as an example of how this framework could have the same inputs but have outputs in terms of a story that differs for three different brands. Obviously this was financial services, but this model works really well across many of the sectors that all of you on the call are, are part of. At this point I’ll turn it over to Paul and he can jump in and maybe lead some questions and see what everyone has to say.
Paul Donagher:
Thanks guys. Got a number of questions actually. Some of them I’ll try and combine a little bit as I usually do, as well as people have kind of asked similar things in slightly different ways. A number of people are asking about B2B versus B2C and do we think about brand health or do we, or is the framework set up differently to take account of B2B versus B2C? I think a lot of people are curious as to how we think about using this framework, using this model and the outputs that it can provide on B2B versus B2C and get you guys comments on that.
Glenn Staada:
I’ve got about 40 percent of my clients in the B2B space. A lot of that in terms of commercial banking and work with advisors. The model is set up so that the issues of salience preference, loyalty, connection will work for B2B. Some of the underlying choices that they may have. The underlying attributes are going to be different. But the idea of looking at where a brand is on a spectrum and a continuum coming to a single score for brand health, in my experience, works just as well in the B2B space.
Mike Patterson:
I think that’s true. Some of the wording in the approach that we’ll take to some of the measures is going to have to be custom modified. Some of the measures may not work quite as well, such as those connectivity or community measures. So, but really it depends on the industry. What we’ve shown time and time again when we conduct a B2B study is to do the modeling. We find that the models work really well, that we have a very good model fit. So yeah, I think it’s applicable both for B2B as well as B2C.
Paul Donagher:
I agree. And I think I would also just add one element to that. We often can make some assumptions that there might be more emotion tied to decisions around B2C and more functional elements supplied to B2B, but we’ve always seen — depending on the sector or the industry — we’ve always seen that that is a balance and that there is often just as much emotion and decisions around B2B and, and really just as much functional requirement around B2C as well. So the two are often similar in that, although the balance will be different. One question, Mike, you addressed this one. You mentioned forward-facing versus backward-facing understanding brand momentum if you like. How do you respond when you might get asked by clients or internal stakeholders or other people who are involved in, in brand health work? This work is typically backward facing. How can we make it more predictive and how can we make it more forward facing and get more predictions out of it for internal stakeholders?
Mike Patterson:
Glenn showed where we will develop our simulators, I think by conducting driver analysis and then putting all of this into these “what if” simulators, it allows us to be more forward looking, so establish say, an overall goal for brand health, and then understand what is likely to happen in the future as we make improvements to specific areas are we likely to see, or what improvements are we likely to see in brand health? It allows you to project out where you’re going to be vis-a-vis those improvements. Glenn, do you have anything to add?
Glenn Staada:
I was going to say the same thing about the simulator tool. That’s very much how we use it to be forward looking. We have programs where we swap out a section of questions at the end for topical information on a quarterly basis, and often those will be forward-looking type questions. Do you foresee having these needs in the future? Do you think this regulation is going to impact you based on the results that come in? We profile the people that say certain things are an issue, how are they feeling about brands versus others? So there’s a lot that we can do that isn’t just backward looking. And, yes, the fact that each of these programs while using this framework are custom, it gives us the ability to do that for certain sectors where forward-looking may be more important.
Paul Donagher:
Appreciate that question here on when there’s an upturn or downswing on communication. So let’s say if we know that we are a brand that is going to go dark for a month or two weeks, and typically they’re heavy spenders or spend has increased as seasonality, and that might have an effect on some of our KPIs. How do you guys take into account this current spend on communications and how that might be and how we might see KPIs being affected by that within any framework.
Mike Patterson:
I find that there’s real value in continuous measurement, being in the field throughout the year so that you can pick up any nuances. But having said that, if a client comes and they know that they’re going to have heavy up periods at certain points in time, we might want to do some additional interviews, boost up our sample size pre and post to see what impact those communications have. As we often do, we’re doing some time series modeling where we might be looking at seasonality or, or other things and, and one of those inputs then could be those advertisement campaigns or, or whatever communication campaigns so we can measure the impact.
Glenn Staada:
I’ll add that we have a mix of different cadences for trackers, some fast moving categories. You know, we’re in the field continuously for those reasons. Other B2B categories that sometimes don’t move as fast. It’s okay to not be fielding continuously, especially those that have finite universes and there aren’t a million CFOs out there that we can talk to. We like to keep that cadence aligned. To the point of this being a brand health framework, it’s not just to measure the effectiveness of communications, it’s to measure how your competitors are tracking trending, how things that are happening in the environment that you don’t have an impact on are impacting your brand and other brands. It speaks to not just designing the field work periods around when you’re going to be spending the most.
Paul Donagher:
I think that’s good commentary and always under having a pulse on the competition for what’s going on there as well. The last question for Glenn is from a brand that has recently added some activity and some brands to their portfolio and they have tracking work that they’re currently doing. How would our framework, or how would we recommend taking account of brands that come into maybe a centralized insights team’s purview that they didn’t used to have, whether it’s through purchase or just through another part of the business? How would our framework deal with adding brands into the portfolio?
Mike Patterson:
To me, it simply becomes another brand. So hopefully in some cases you’ve already established those newly added brands within the tracking framework. But if not, it feels like you would simply add those into the brand list. Because we’re always measuring both our client brand as well as competitive brands, right? So we have those, those benchmarks, and so I would add those in as additional brands that we would want to start to track.
Glenn Staada:
Yeah, the only build on that I’d have is you also want to consider whether the brand has a different target. If it’s different, it extends your addressable market. Are these brands focused on the market when maybe your brands weren’t? So you may want to augment the sample. I don’t know if there’s a regional element, but looking at what the new brands do and is there a need to augment the sample plan? If that was the case, I’d probably recommend you keep the sample constructs that you have so you’re not messing with the trendability of your existing program, but you build on it in a way that’s complimentary, but you’ve still got the existing program as a whole and you can measure that.
Paul Donagher:
I think I agree with that. You have to be able to continue to track and trend, but using perhaps the idea of this as the benchmark way of anything new that’s coming into the program. Glenn, well look, that’s all the questions that we have folks. Thanks everybody for your time today. We’ll send out a recording of this that you should feel free to share or listen back to. Feel free also to get in touch with us. We will be back with our webinar series in Q1 next year with some new thoughts, new topics, and new ideas. But in the meantime, thanks everybody for your support and the webinars that we’ve had in 2024, and I hope everyone has a safe and happy holiday season. Thanks everyone. Thank you. Thanks all.
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