Why do we see smart, intelligent world class branded players such as Unilever spending large/ disproportionately large amounts of their A&P budgets on social media versus traditional media? Do you have any insight as to why they might be doing this?

We agree with you, with research evidence building, moving away from traditional media and allocating more budget to social media increasingly seems to be a silly decision for advertisers. However, it may make sense that this is happening. The evidence does take awhile to trickle down into industry practice and the arguments for using social platforms are logical and (at least on the surface) seem appealing, even if they are wrong.

Linear TV audiences are obviously in decline and this has been the case for some time. Even prior to this decline, however, proliferation of channels and fragmentation of the audience across more platforms had meant the “vast and fast” reach benefits that had been the key reason for advertising on TV were becoming less powerful. Advertisers more commonly would split their budgets over more media (which now includes social), just to deliver the cumulative reach they would have once been able to deliver in just a few TV placements. Furthermore, Double Jeopardy applies in media just as it does brand buyer behaviour, so when there are new entrants, they inevitably steal share from the big incumbents (i.e. traditional media).

However, this still doesn’t explain why advertisers are choosing social media as they move away from the traditional options, especially when research tells us that social (and similarly influencer) platforms attract heavy user audiences with high frequency exposures (which, as you allude to in your question, is not all that desirable for brand growth).

From a reach point of view, social media makes impressive claims about the size of their audiences, which is appealing for practitioners.

Social media monetises their offering based on impressions, so it is in their interest to claim as large an audience as possible. But impressions is a long way from being a “clean” measure of audience size. Rather, it is diluted with both the frequency of exposures (2 impressions could be 1 person being exposed twice, or 2 people being exposed) and by ad fraud (i.e. bots and the like, rather that real potential buyers once). Furthermore, social media is not one single “channel”, but rather a massive suite of options. Your ad on Meta, for instance, will not reach the whole Meta audience, but rather a far smaller sub-segment of that audience. So, while on the surface, social media looks like they have large audiences for advertising (potentially providing a return to the “vast and fast” reach Linear TV used to offer), this is sadly not actually the case.

A second argument that social media proponents make is that audiences trust the source of the promotional message more (such as with influencers or friends delivering those messages) than they do the more traditional advertising mediums. And with trust (it is further assumed), comes heightened impacts from the advertising.

Again, this sounds logical, it is just a shame it is not supported by the evidence. Audiences may indeed trust those delivering a social media advertisement, but it is a stretch to say that then makes our brands trusted. And brands do not have to be trusted (beyond being available and thus an acceptable example of the category) in order to be bought.

Related to the trustworthiness of the source of advertising messages, is the suggestion that social media are better able to place advertising adjacent to related content.

The rationale here is that an ad placed within relevant context will be more impactful on its audience. Again, the evidence that this is the case is lacking. Programmatic buying of ad space has technological appeal, promising to reduce wastage by reaching only those people sending digital signals that they are about to buy. However, advertising works by building long term memory structures for the brand, rather than by delivering immediate sales impact. It is therefore helping the brand to establish its Physical Availability, but this is not advertising.

This brings us to another potential reason why advertisers appear to be moving away from traditional platforms and towards social media, and that is because (again on the surface) they look cost effective.

Social media (particularly in the influencer space) can offer a cheap alternative for content creation, although many advertisers also simply re-purpose their video content. However, they also seem to be cost effective based on the money spent and for the sales that are then attributed to that expenditure. In our experience, increasingly advertisers are looking to ROI (either through Media Mix Modelling or simply by looking at sales data). Because social media reaches audience of heavy users who likely would have bought regardless of their advertising exposure, social media can look very efficient, when in actual fact it is successful in delivering on Physical Availability more so than efforts to build memories to nudge sales in the longer term.

The following commentaries, reports and papers on our website may provide some additional relevant reading material on this topic for your interest.

This answer to a sponsor question is about digital advertising more broadly, but has some points about social at the end: What is the Ehrenberg Bass guideline for an effect digital strategy?

This article speaks to the skew of heavy users in social media audiences: What’s Not to “Like?” Can a Facebook Fan Base Give a Brand the Advertising Reach It Needs?

This report looks at social and TV advertising when used in combination: Combining tv and social media advertising beyond 30 report

The following thesis and commentary also covers why social has become so popular, and what it can and importantly what it can’t do for advertising practitioners:
Stand out or get lost. An analysis of social media advertising effectiveness
Social media is not a viable advertising medium yet

E.R.
28 March 2025

I was reading through some social media related FAQs and wanted to find out more about the service in development that measures reach across media highlighted below – can I trouble you to point me in the right direction for where I might be able to find out more about this service? We caution brands relying on the social media companies ‘marking their own homework’ in providing metrics on reach. We have a new service in development that measures reach across media. What are the implications in social media for growing mental availability? Do we view it as a valuable channel for growth or is the reach too small?

As you would be aware, in order to be effective communications campaigns need to reach an audience and with few exceptions the larger that audience, the better. Extant evidence shows that reaching an additional potential buyer has more impact than reaching existing audiences repeatedly (i.e. with high frequency).

We have long had a dilemma in media measurement, however, in determining the size of the audience when a campaign is spread across platforms. That is, it is proving increasingly difficult to measure reach supplied by the different platforms being used in a single campaign. This has only become more pressing as the number of available advertising platforms has increased, media audiences have become more fragmented and advertisers has sought to maximise the reach of their campaigns by using more platforms for their communications.

Social (and other digital) media are particularly susceptible to this measurement challenge, because platforms report impressions (rather than reach), which are known to contain considerable ad fraud (i.e. bots and the like) and because frequency of potential exposure is not extricated from the audience numbers (i.e. reach). Added to this, each platform determines their own impression numbers (marking their own homework as you point out), and as such they are often unrealistically high. This is especially noticeable when the impressions bought across all platforms in the campaign are summed. They very quickly suggest the campaign reach well over 100% of the market!

To address this issue, we have investigated the potential for a survey-based ad recognition metric (which we coin “Brand Reach”) to provide an indication of when ads have had sufficient impact on the audience that they created a memory. This allows us to identify the cross-platform duplication in the size of a campaigns audience, and more appropriately evaluate the value of each platform. It is a fairly simple approach, but one that addresses the measurement issues outlined above and also gets at the heart of what we should expect our advertising campaigns to achieve (i.e. to form and then nudge memories).

We have tested this approach with several of our sponsors and also with our very own advertising campaigns and have seen that for social media campaigns cross-platform reach duplication can be more than 40% (Meta, LinkedIn, X, etc)! Thus, social media impressions can significantly inflate the reported size of the market for advertisers, leading to incorrect assumptions about how much these platforms are adding value to our campaigns.

Advertising is indeed about building mental availability, and all advertising (including social media advertising) will contribute to that. However, when we consider the opportunity costs (both financially and in time) that come with choosing between platforms, media that can deliver a large, real (i.e. not bots) and unduplicated audience should always be our priority. If you’d like to get a better read on just how much cross-platform reach duplication is happening for social (and other) advertising campaigns at the Singapore Tourism Board, perhaps we could get on a call and discuss Brain Reach measurement in more detail?

E.R

22 November 2024

Is there any research that can help us answer some questions on social media influencers and the impact that they have on the purchase funnel. Should these be used to build awareness or drive consideration?

To answer this question, it is important to keep in mind that the purchase funnel suffers from one key limitation, which is the risk of placing excessive emphasis on the middle and bottom of the funnel (driving consideration and conversion), overlooking the strategic importance of the top of the funnel, where wide-reach marketing tactics should be deployed to attract all types of buyers, including non-buyers – a vital requirement for brand and market growth. Influencers, like social media campaigns in general, tend to appeal to customers at more advanced stages of the purchase funnel, simply because: i) ‘followship’ and social media activity/engagement skew opposite to buying behaviour, with most users interacting with social media content being already existing customers/somewhat loyal to the brand behind that content; and ii) algorithms underpinning the selection of content served to people on social media (including content by influencers) automatically pick-up on existing intent and behaviour (e.g., search intent, content viewed, content interacted with, lookalikes etc.) in alignment with more advanced stages of the purchase funnel. Therefore, although influencers, like any other marketing tactic, should be used to build brand awareness (or any other top of the funnel strategy), they are feasibly more prone to impact the middle and bottom of the purchase funnel. 

Working with influencers calls for two sets of strategic decisions:

• Branding decisions – You need a ‘fit’ between the influencer and the brand. As the influencers marketing is coming of age, this process is resembling more and more a standard endorsement process, often agency-led via a brief. We recommend an evidence-based approach testing influencers as potential Distinctive Asset (hence, to figure out the potential for growing Mental Availability) and evaluating influencers’ potential as sales touch-points for social commerce (Physical Availability).
• Media planning decisions – Like any other media decision, classic advertising principles of reach and frequency lead plans and budgets, as reflected also in influencers’ rate cards. Hence, although it is widely accepted that engagement is quite low across most social media platforms (including when working with influencers) and that the number of followers can be misleading, managers still find themselves needing to evaluate theses typical social media KPIs and resulting trade-offs. Unfortunately, there is a lot of contrasting evidence both in scholarly research and industry reports on this point, with unclear advice such as:

• Choosing influencers based on the sheer ‘size’ or their followers’ base (e.g., preferring celebrities and media influencers) to maximise reach > problematic strategy because influencers of this size have limited to no engagement for their size. 

• Choosing influencers based on the engagement potential and the intensity of interactions with followers (e.g., selecting everyday influencers and content creators) > also a problematic strategy because it implies repeated exposure to the brand but just with a very small (near nil) % of category buyers. 

The evidence used to provide these recommendations is also based on small datasets based on single instances of influencers and social media platforms, which limits generalisability and benchmarking. Between 2018 and 2022 the Ehrenberg-Bass Institute has addressed this issue creating and analysing a unique set of data with the following characteristics: 

• 180 influencers with varying size (i.e., in terms of the number of followers), including an equal number of celebrities/mega influencers as well as micro/everyday influencers.
• 5 social platforms including mature vs. growing platforms and platforms undergoing significant changes at the time of data collection (Facebook, Twitter, YouTube, Instagram and TikTok).
• A sample of 35,000+ posts, with engagement rates randomly derived from 20 posts p/ influencers (industry stats usually use the last 5 posts).
• Double Jeopardy analysis to explore observed and expected trade-off between the share of followers and the engagement rate of each influencer within the platform/sample and within specific areas of expertise such as beauty and fashion, travel and lifestyle etc.
  

The main findings that we extracted lead to the following recommendations:

1. Decisions involving influencers should be platform specific and industry/areas of expertise specific.
2. DIY: For greater generalisability of findings and benchmarking purposes, the number of followers and the engagement rate can be robustly recorded from publicly available data, which can then be analysed using a classic law of growth: the Double Jeopardy.
3. For mature platforms such as Facebook, Twitter and YouTube, there is a reverse Double Jeopardy pattern: influencers with more followers return the lowest engagement of all. Hence, on these platforms, it is best for brands to collaborate with smaller influencers and content creators.
4. For growing platforms such as TikTok, there is a standard Double Jeopardy pattern: influencers with more followers have also greater engagement. Hence, in this instance, brands can choose influencers based of wide-reach potential.
5. Platforms undergoing changes like Instagram reveal no clear or predictable trade-off between the number of followers and engagement rates of influencers.

   Therefore, it makes sense to choose influencers based on their wide-reach potential. 

Recommended read: Pourazad, N., Stocchi, L., & Narsey, S. (2023). A comparison of social media influencers’ KPI patterns across platforms: Exploring differences in followers and engagement on Facebook, Instagram, YouTube, TikTok, and Twitter. Journal of Advertising Research, 63(2), 139-159.

L.S
5 Sept. 2024

I am scoping some work related to measuring Category Associations in mass (TV, radio, print) as well as non-mass (social, direct mail, email) channels. We are often asked if specific creatives are likely to drive this perception.  

We have been piloting several approaches (e.g., lift, aided/unaided message recall, etc.) in mass and are looking for how to roll this out to other non-mass testing. Would love to get your perspective on whether this is likely to be fruitful and/or if there are any considerations we should keep in mind as we set out to measure Category Associations in creatives.

Also, given the scale of social media options, formats, platforms, impressions, and other complexities involved in social testing, do you have any thoughts on methodologies/tools to measure social performance at the creative level? Any best practices to consider?”

Thanks for the question, this is something that has been on our mind and we are currently looking at ways to assess this in advertising.

Our belief at this stage is that:

1. A key metric should be about message clarity which is the degree to which everyone who sees the ads gets the same message and therefore builds the same brand associations.
2. An unprompted message capture approach is important so we get what are the associations likely to be built and not just put words into people’s mouths. The danger with prompted approaches is that they will also revert to the general impression of the brand in cases when the message is not clear, and so obscure our ability to detect this.

But we propose doing this at pre-test stage rather than in market as messaging is something you want to get right beforehand. So just showing to a smaller sample of category buyers and asking what they think the ad is saying to them.  We are currently working on testing different wording to see how much that matters.

We are also currently testing the types of execution of the message that lead to greater message clarity (is spoken better than written, are images better than text, is one message better than multiple, how much do people infer messages). No findings on this yet as results are very preliminary.

We also have some work coming out soon showing that the clearer the message the more likely you are to drive the link to specific associations.

In regards to social media testing, do you have any general guidance? We produce thousands of pieces across the various lines of businesses, some produced by our ad agency and some internally. We also have organic media. The whole thing is very overwhelming. I think the best place to start are those that mirror our mass-media led creatives with the most impressions, but curious if/how you all have been thinking about social creative testing/measurement.

I would first ask the question:

Why are we producing so many different pieces with so many different messages? Is that an efficient use of resources?

Next I would try to get some guidelines in place, by testing as series of different creative styles to work out what works (or you can wait for our R&D findings), so there was less chance of an ad being a messaging dud.

Overtime there will be some that you don’t need to test because they use the ingredients that work, it will just be when you deviate from those you need to check you have not gone too far.

You don’t need a bit sample for message testing, 100-200 is likely enough. So each piece is not that onerous, but yes it could easily mount up.

J.R

21 August 2024

Does TV drive more reach and higher brand recall than YouTube ads?

We need more head-to-head comparisons of YouTube advertising versus TV advertising, using single-source sales as the dependent variable. But in one of the Institute’s Beyond :30 studies YouTube exposures had higher rates of brand recall than linear TV ads and Facebook ads (Bellman et al., 2023). Whether to buy YouTube ads or not depends on their unduplicated reach, compared with TV (Romaniuk et al., 2013). If TV is reaching 80% or more of all category buyers, there would be no need to buy YouTube ads. 

References

• Bellman, S., Rask, A., & Varan, D. (2023). Is news a good context for advertising? Beyond :30 Study 88
• Romaniuk, J., Beal, V., Uncles, M. (2013). Achieving reach in a multi-media environment: How a marketer’s first step provides the direction for the second. Journal of Advertising Research, 53(2), 221-230 

S.B.
14 March 2024

What is the best practice on frequency for media touch-points? For something like TV vs social vs programmatic, what kind of frequency capping should we follow.

There is some generalised evidence around the potential impacts of exposure frequency (regardless of whether that is in a single media or across touch points) that will be helpful here.

The idea that there was a need to be exposed to advertising messages with frequency came from the psychology literature originally, suggesting that in order to learn something people need to be exposed to it multiple times.

In media, this was called Effective Frequency and a number of 3+ exposures was thought to be the threshold. However, evidence that buyers have to “learn” in order to buy brands, is lacking. To the contrary, Single Source analysis shows that the greatest uplift in sales impacts of advertising typically occurs from the first exposure in a window (i.e., 1+ reach in a month), with diminishing returns from subsequent exposures (this is shown in the chart below).

As a result, we recommend that you worry less about reaching a potential buyer multiple times across touch-points and more about reaching additional potential buyers. This will give you the greatest potential for aggregate level advertising impacts.

Some additional considerations:

Firstly, in most markets, we don’t know when a particular individual will buy, because buying behaviour is heterogeneous and ad impacts decay, so we can’t just advertise once and never again. Our advertising needs to be continuous (i.e., spread across time), in order to reach as many potential buyers as possible as often as possible. Exposures (frequency) that is spread over time is continuity. Exposures which are spread are more valuable than those that are burst (more chance to intercept as if random buying, get light media users and improve memory effects).

Campaigns inevitably results in some frequency for those who do see our communications (some people are very heavy media users compared to others). Aim is to minimise excess frequency where ever possible. Using big media, popular programs etc. can help.

Secondly, not all reach is equal. As you point out, there are different touch-points, and a touch-point that is closer to the purchase may be more impactful than touch-points that are further away from the purchase, because we do know that recency of exposure helps with impact (Report 57: A Guide to Continuous-Reach Advertising). However, there is an important distinction to be made here between advertising (which helps build and refresh probabilities of purchase (i.e., Mental Availability)) and communications that help make the most of a buyer who has already decided to buy. Activations are more about ‘catching them when they fall’ in that the buyer has already recognised a need to buy and this may just be that final message to reinforce behaviour that was in all likelihood about to happen regardless. You need to be there at these times and touch-points, to the point where you get your fair share.

Our recommendation with your communications is to optimise unique, unduplicated reach as much as possible. This sometimes means adding touch-points to your campaign, advertising across media/platforms, and in turn delivering some exposure frequency as audiences who are exposed at one touch-point, also see the advertising at another point. When planning to maximise overall reach, start with the touchpoint or media that delivers the most potential categories buyers, adding to that with the objective of reaching unique audiences (potential category buyers) as much as possible (references below). Adding digital to a TV campaign, for example, may be better than adding two channels of TV if that gives you access to an audience not available on TV.

So directly to your question, in relevant media cap at 1 OTS if scope to still exists to build unique reach for the relevant window. If budgets allow, more exposures are better than less but with diminishing returns and spreading those exposures is better than bunching them (especially if it means you go dark later).

Achieving Reach in a Multi-Media Environment. How a Marketer’s First Step Provides the Direction for the Second

Cross Platform Frequency (Beyond :30 Report)

In summary, you should be aiming to maximise reach (spread exposures across buyers and across time) for all campaigns, as that will be optimal for impact.

E.R.
7 February 2024

I see and hear a lot of generalist talk about how Gen Y & Z are way more engaged with brands and their content via social media.

Has the Institute conducted research on variations in brand engagement (in terms of loyalty, media consumption, buying behaviour) across different life stages?

Some facts and figures from the Institute itself were published in a Journal of Advertising Research article a few years ago, but are still relevant today (Barwise et al., 2020). In that article, we obtained Nielsen data in 2017 to compare younger television viewers (aged 18 to 34 years) with older viewers (35 to 54 years). Those born from 1981 to 1996 (aged 21 to 35 in 2017) would be Gen Y (Millennials) and those born later (aged 18 to 20 in 2017) would be Gen Alpha. These younger television viewers were different from the older viewers because they watched less live TV and more online TV (via smart TVs and connected-TV devices, or other online devices, such as PCs and smartphones). Compared with 18-34 year olds in 1992, 25 years earlier, the 2017 18-34 year olds watched slightly less TV (live + online) per week (29.1 hours per week vs 30.1 hours in 1992, a 3.6% reduction). In contrast, the older group (35-54) had increased their TV hours (live + online) per week (from 33.3 hours in 1992 to 38.8 in 2017, a 17.5% increase). We can probably assume that 18-34 year olds in 2017 dedicated as much of their week to media consumption as 35-54 year olds, and that the nearly 10 hours difference was absorbed by consuming social media and other alternatives to television.

This suggests that advertisers need to use other media in addition to television to reach Gen Y and Gen Alpha, such as social media, radio, and out-of-home.

Which social media to use to target younger people changes when they migrate to alternatives less likely to be used by their parents. Currently, a Statista report from October 2023 shows that most (68%) of the audience for TikTok was aged 18 to 34. Only 25% was aged 35 to 54.

These numbers are about media usage, and useful for deciding which media to use to reach consumers of different ages with advertising messages. Another of our Institute articles suggests there are no differences between age groups in brand usage (Anesbury et al., 2022), which should be the main metric for brands to consider.

References:

• Anesbury, Z., Bellman, S., Driesener, C., Page, B. and Sharp, B. (2022). Ageism Kills Brands. Australasian Marketing Journal, 30(4), 364-370.
• Barwise, P., Bellman, S. and Beal, V. (2020). Why Do People Watch So Much Television and Video? Implications for the Future of Viewing and Advertising. Journal of Advertising Research, 60(2), 121-134.

S.B.
11 January 2024

Social media give the opportunity to Brand Leaders to be the Voice of the Brand. Is there any evidence that this PR effort is determining an impact on Brand saliency, meaningfulness, reach and growth as a consequence? In other words – can this replace advertising spend?

We take Brand Leaders to mean influencer voices in the social media space.

Like with any media decision, we encourage the classic advertising principles of reach lead plans and strategies (see our Best Practice Media Principles report for more detail).

When considering reach of influencers, it is common to consider the sheer ‘size’ of their follower base as a proxy for reach. However, this can be problematic as not all followers are reached with influencers content.

We know brands grow by reaching all potential category users, so media choice should leverage the best possible reach a budget can afford. In most markets, TV can achieve fast and vast reach, where comparable reach in social media may take much longer.

In terms of whether social media can replace advertising spend, we would recommend considering the cumulative reach of your media tactics. As outlined in Best Practice Media Principles report, we encourage planning to start with big reaching media first, then for complementary media that provides unique reach to be added to the media plan. Each media dollar should work towards reaching category buyers that have not been recently exposed to your advertising/marketing efforts. So, in terms of whether social media can replace advertising spend, consider the viewing habits of your category buyers. Where can most of them be reached? Is it that more cumulative reach is achieved with TV as the primary media, and social media is able to reach category buyers that TV finds hard to reach (see also our report on light TV viewers).

An FAQ’s from our website that may be of interest: How to measure the effectiveness of ‘influencers’ as a media vehicle?

And an academic article ‘A comparison of Social Media Influencers’ KPIs Patterns Across Platforms’.

K.V. and S.D.
28 March 2023

Looking at different global reports, consumers below 30y hardly watch TV. Social channels in terms of media spend are growing. Global brands work more with influencers (Cola, Pepsi). Can you share your opinion on working with influencers? Is it better to work with them in a long-term perspective (1y contract) or just one post can replace standard communication channels like TV?

Working with influencers calls for two sets of strategic decisions:

• Branding decisions – You need a ‘fit’ between the influencer and the brand. As influencer marketing is coming of age, this process is resembling more and more a standard endorsement process, often agency-led via a brief. We recommend an evidence-based approach testing influencers as potential Distinctive Asset (hence, to figure out the potential for growing mental availability) and evaluating influencers’ potential as sales touchpoints for social commerce (physical availability).

• Media planning decisions – Like any other media decision, classic advertising principles of reach and frequency lead plans and budgets, as reflected also in influencers’ rate cards. Hence, although it is widely accepted that engagement is quite low across most social media platforms (including when working with influencers) and that the number of followers can be misleading, managers still find themselves needing to evaluate theses typical social media KPIs and resulting trade-offs. Unfortunately, there is a lot of contrasting evidence both in scholarly research and industry reports on this point, with unclear advice such as:

– Choosing influencers based on the sheer ‘size’ or their followers’ base (e.g., preferring celebrities and media influencers) to maximise reach … problematic strategy because influencers of this size have limited to no engagement for their size.

– Choosing influencers based on the engagement potential and the intensity of interactions with followers (e.g., selecting everyday influencers and content creators) … also a problematic strategy because it implies repeated exposure to the brand but just with a very small (near nil) % of category buyers.

Working with influences should take a long-term perspective to ensure category users come to associate the brand to the influencers, building and reinforcing wider, fresher networks of associations in memory and hopefully growing mental availability for the brand. One-off collaborations such as a single-post would be costly and non-sensical, given the fickle nature of social media (level of clutter).

Social media is yet to replace TV for advertising purposes. While the sheer potential reach might be comparable in some contexts (e.g., Facebook vs. free-to-air TV in some countries like the US and Australia), effective branded reach is still not comparable. There is also a risk of skew toward specific demographics based on the user base of the various social media platforms, some of which are different.

L.S,  N.H & K.V
24 January 2023

I would love to get the Ehrenberg-Bass scientists’ point of view on the role of Social Listening tools to measure progress making on Brand Mental Availability and as a way to approach Brands’ Associative networks.

Indeed, we know Mental Availability is a reflection of the quality and quantity of buyer’s memory structures devoted to the brand. We also know the more extensive and fresher the network of memory associations, the greater the brand’s chance of being thought of or noticed in the variety of buying situations experienced by buyers. We currently use a survey-based approach to measure and operationalize Mental Availability, and because things move slowly we deliver data once a year. However, marketing activity is intense and brands are challenging Insights teams to get a more frequent read, and we do not want to start delivering MA metrics frequently because people could over-react to them. Instead, we are considering completing our traditional approach with a social media monitoring tool which could show us what people say about our brands and if our memory assets are the ones we expect consumers to talk about.

Indeed, looking at metrics that are related to Mental Availability at short intervals – or indeed, monitoring interactions with the brands through social media monitoring, may risk the business reacting to matters that are transient in nature. This does not mean that you shouldn’t keep a finger on the pulse when it comes to changes in consumer sentiments and preferences, so information gained through your social monitoring tool can be used to supplement your core Mental Availability measurement. Structured periodic Mental Availability measurement (e.g., on annual basis) remains very important.

In interpreting the sentiments, the business would also need to be aware that Words of Mouth (including eWOM) are likely to be expressed by heavy brand users (see here), light buyers that represent the majority of the buyers are unlikely to contribute to the discussions captured by the social monitoring tools. This needs to be considered so that brands don’t unnecessarily respond to the wish of new flavours or features that are skewed towards coming from the heavy buyers, rather than the majority of buyers. However, insights such as patchy distributions, barriers to purchase, key competitor activities, or sustained changes in market sentiments (e.g., products with less sugar, increased convenience) may help the business in improving mental and physical availability, managing the brand and product portfolio, and directing future innovations and new product developments.

I hope this helps.

A.T.
9 May, 2022