- Choose the right targeting for your company size and brand lifecycle stage
- Define the optimal audience size
- Measure the effectiveness of different audiences
Hello, Stephanie, and welcome to the show.
Hey, Anna, thank you so much for having me.
It’s awesome to have you here. Today we have yet another exciting topic for our listeners, and it is all about brand and how to set up, track, and optimize the right audience for a brand. So my first question to you, Stephanie, would be, what are the very first steps you as a marketer would need to take to define your brand’s tracking audience?
Yeah, absolutely. So I would say this depends on a variety of factors, stuff like brand size, the life cycle of your brand, and also your product category is really going to impact what audience you should be thinking about to set up a tracking brand tracker for, for example, if the size of your brand is relatively large and well-established. So by size, I mean the general brand. Awareness levels of your brand are high, so people know your brand, they’re aware of it, they recognize it on the street.
Then keeping an eye on the general population might be more useful to you as well as having perhaps the ability to segment the population by your target audience as well. So having an eye on the general population can be useful in cases where you would like to keep a pulse on the wider awareness of your brand or assess growth opportunities and areas for your brand to grow in. Limiting it to something like a very, very core target audience that’s only relevant to the people who buy your brand then kind of limits your ability to grow outside of that as you enter new life cycles.
Conversely, a small awareness brand, say someone who’s quite limited, brand awareness is not very well-known and well recognized, maybe is new to the industry as well. They will likely find that this general population overview is too widespread to pick up on subtle brand changes. And most of the data will be relatively meaningless as most audiences will not be relevant to their brand.
So here, it’s best to begin with a more targeted audience approach, so focusing on those who are likely to be exposed to your brand often and who are likely to be your primary target audience as well. I would say product category is also important to consider when deciding on an audience. Certain categories might only be applicable to a certain demographic. Therefore, tracking an audience outside of this is also pointless because your brand will never attempt to reach these consumers. So a good example of this might be something like a women’s health product or men’s beard products where only a specific gender is actually applicable to the
All right. Awesome. I really love how you’ve outlined three components, like brand size, product category, and brand lifecycle stage, influence these decisions. And you’ve also talked about comparing the general population and measuring brand awareness versus measuring the effect a brand has on a specific target audience.
So if we could dive a little bit deeper into this, when should a brand compare their target audience and a general audience, and why could you expand on a couple of examples in which they should make this kind of comparison?
Yeah, of course. So at Latana, often we do accommodate this kind of view, as you mentioned. So looking at a total general population sample but with the additional feature of segmenting by more specific data and defined to an audience. We refer to this as a custom segmentation in the data set. So this is where we’d have a general overview and then a custom audience as a filter for your data set.
In this case, it can be really useful for brands to have this comparative view of their wider awareness and perception levels for long-term tracking against that of their core consumer to which their brand messaging and product positioning is aimed. So a good example might be something where we compare the general population’s perception of a brand such as IKEA, compared to the perception of young adults with maybe a mid to high income who are interested in sustainable and convenient furniture.
So this then helps brands to identify if and where their marketing campaigns are effective and direct their growth avenues towards this as well. It’s kind of impossible for a brand at any one time to reach absolutely everyone in the world. So often, with these kinds of models campaigns, brands will often have a targeted audience who they’re trying to reach. So with this segmentation element, we’re able to track both that kind of vision, where we are looking at where the brand’s really aiming their messaging and their product positioning towards, but also in the longer term, not neglect the view of having a general population overview.
This will really help with things like brand awareness where you want to track the overall awareness growth of your brand, it’ll also help you to focus on maybe audiences you haven’t considered before, which are growing interest for your brand as well. So it gives you that discovery phase for an audience, as well as focusing on your real core audience, who you want to keep a pulse on continuously.
Awesome. That sounds really interesting. I really like all these different angles in which you look at the brand through the lens of an audience. And now, let’s dive into the actual measurement part a little bit more. So how should market errors define the optimal audience size first of all, and how can they ensure that they are tracking and capturing brand movements reliably through these measurements?
Yeah, absolutely. I think the main thing we focus on for reliability is the sample size. This is something that we are very strict with Latana, because it’s probably the most important factor to consider if you want your data to be both representative and reliable. So we always begin with a total minimum sample size of 1,000 people. And this is for a general population overview or if they might have a custom sample.
So they might only target women, for example. We’d always start with a base size of 1,000 people. And segmentations, as I mentioned before, might have this segmentation of their audience. The minimum sample size we offer there is 500 as well. Of course, the bigger the sample size, the more accurate the insight will be and so less uncertainty in the data. Really comes from having a bigger sample size basically to be more representative.
These are the minimum sample sizes we work with, 1,000 and 500. Suppose a brand has low awareness levels as well. In that case, it is even more crucial to have a robust sample size as each and every change in the data over time will be represented more significantly, and it could be difficult to interpret meaningfully if we have a very low sample size, to begin with. Because if you imagine brand awareness for a brand with very low awareness basically if they start with only 1,000 data points and their brand awareness is only 10%, then we’re only really allowing 100 people to have meaningful insights about the actual brand further more than awareness.
So really starting in a big pool of people, then allows you to of a bit more of a deep dive into the brand tracking element, so you might want to capture further down the line.
All right. That sounds awesome. And thanks for sharing all the ballpark numbers because I think this would be very useful and valuable for the marketers out there to start to design these campaigns. And now, let’s talk about the KPIs more specifically.
So, which KPIs can you track to measure how the audience responds to our campaigns? Maybe continuing from these conversations about the sample sizes, so how would you ensure that the population of the right size is responding to your brand messaging and then giving you concrete cues on what you should focus on next?
So I think tracking impacts from campaigns is very different from tracking general brand health over time, and so, therefore, it does really require a more specific setup and methodology. Some trackers tackle this by asking direct questions within the survey to assess campaign awareness and perception. So, for example, they might ask, have you seen adverts from this brand in the past week, or what did you think of these adverts that you saw? Where did you see them from?
We don’t really believe this to be a totally effective capture of reality because respondents often find it incredibly difficult to recall specific instances of advertising really unless it’s very persistent, it happens at a very memorable time, or it’s a very, very, very well-known and recognizable brand. So an effective way to capture advertising might be recognizing Coca-Cola adverts around Christmas time. This is a very big brand, it’s very synonymous with Christmas time, and that’s a very amazing capture for respondents.
So they might be able to do that. But when we look at quite small brands that don’t have very good awareness levels, having seen these adverts passing you by on the internet or on TV advertisements or out of the house, asking people to remember if they saw these adverts in the last four weeks is really, really impossible for the respondents to accurately answer on.
So for our clients, we want to ensure that we capture increased sentiment or impact in the right way. We instead use two KPIs to capture impact, firstly, the overall awareness of the brand, and secondly, associations with the brand. So basically, from the campaign, has the brand awareness of the brand increased? Have more people been seeing the brand and recognizing it and that the logo is triggering their recall of the brand? And have the associations or people aligned with the brand changed based on campaign messaging?
So, it might be a brand focused on sustainability, more people are linking that brand with sustainability since that campaign came live. So we want to measure those two KPIs in that specific way. We also slightly differ on renditions of this campaign impact as well. So which brands might instead want to focus on if a specific channel was effective at reaching their audience or not.
So rather than before, we focus really just on the pre and post-campaign impact, so whether a campaign had an impact on an audience or not. In this indication, we would actually focus on whether the specific channel they used was effective at reaching the audience.
So the KPI setup is actually very similar here. We want to compare awareness and associations again, but here we would be comparing two groups of audience, those who regularly use the marketing channel, say, for example, Instagram users perhaps, and therefore likely exposed to the campaign more so than another audience versus those who are non-users. So non-Instagram users versus Instagram users to assess the different awareness levels and association levels, whether that significantly increased for the target channel or not.
So we have a very specific avenue to look at campaign tracking versus brand tracking in general. In general, if anything, a little bit more increased for campaign tracking, and you do need to be a bit more specific as well in terms of the audience, you’re reaching. So, for example, most of the ways that we would capture campaign impact would be through a city tracking approach, so you really want to look at the exact relevant audience to that campaign.
Brands might run a kind of nationwide campaigning, however, it’s likely that they are focused on specific cities in which their brand awareness is slightly higher maybe, or their target audience is a little bit more specific. So there, we would really want to make sure that we’re capturing a very granular level of the audience. So city tracking, increased sample size, and having the right KPI set up is really, really crucial.
All right. And you’ve mentioned that there are different approaches to measuring different types of campaigns, so a brand campaign versus a very narrow, maybe product-specific campaign, can you please tell us more about the measurements? So what are the typical mistakes marketers make while measuring the size and success of their brand audience?
Yeah, of course. So I think the first one, which is quite obvious, I think, is having a very small sample size. So if you’re trying to measure brand impact or campaign impact, really having a very small sample size is not going to give you any kind of benefit here. You want to be able to pick up on very small brand movements, especially if you have a low awareness brand that we are considering.
So here, we really need to exaggerate the sample sizes to have that representativity and the reliability in the data. I think another thing is going to niche with an audience at the start of tracking as well. So, of course, we mentioned earlier that having a targeted audience can be quite helpful for some small brands, but then the opposite is kind of true to limit yourself too much if you go very, very, very niche with an audience straight away. So it’s only going to be the audience that your product is already existing within because, in this respect, you’re not going to be able to capture anything outside of that or look at any kind of growth avenues for your brand.
So going very, very niche with the audience can be quite difficult. It’s also extremely expensive and time-consuming to access those respondents as well. If the incidence rate of that audience is very, very low, then it can be very difficult to try and get enough data from that audience wave on wave. I think the other side of it is also going too wide if you have a very small brand.
So going with a total general population overview from the very start without any kind of segmentation onto your core customers, that might be also a bit of an error because the data is going to be very, very non-moving wave-on wave. So you’re not going to pick up on much to really, and your brand awareness might stay quite low and quite stagnant for quite a while. So it’s not going to be super meaningful insights for your brand either.
I think on KPIs as well. So that’s more on the audience side, on the KPI side, so what you actually want to track as well. The common mistakes are probably going far too in-depth with questions. So stuff like brand satisfaction, brand usage, NPS scores, these things are only really accessible to brands with very, very high levels of users. Otherwise, that audience that you pick up in your brand tracker is probably going to have quite a low number of brand users in it already, so these people won’t be able to answer about brand satisfaction or MPS, in which case you need the respondent to have experienced the brand already to be able to answer it, so really having very in-depth questions, which can be quite limiting on the audience basically.
Here, I think it’s better to begin quite small, so stuff like brand awareness, category drivers, and maybe category consideration. These kinds of things can really set your brand up to the right mentality of thinking. You can track awareness of your brand over time, which can be super useful to see whether you are growing and what audiences you’re growing within. Category drivers can be a really, really interesting insight into what the audience expects and wants from the category, so whether your brand and your product positioning are aligning with what the audience already wants from the category.
So maybe the highest kind of drivers cost for a certain category, and maybe your brand is actually focused on quite premium products or something like that, it can really help to drive a different brand messaging or different product positioning. I think consideration is also a good one to move into. Once you grow your brand awareness a little bit more, then you can start looking at whether people are considering your brand above others for usage as well.
Stephanie, these are really awesome and very specific tips. Thank you so much for sharing these. And if the audience would love to learn more about you or your work, where can they do it?
Yeah, of course. I think the first place to redirect people to is our website, so www.latana.com. Here you find some really, really good resources, such as brand guides, white papers, and customer testimonies as well. You can also book a demo here if you want to explore our dashboard tool or talk more about the tracking data that you would be interested in. And of course, we’re all over social media as well, so LinkedIn, Facebook, and Instagram. So you can find us in many places.
Fantastic, Stephanie. Thank you so much for coming to the show.
No worries. Thank you so much for having me.
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