Establishing incrementality is critical if you want genuine brand growth. Why? Because many performance platforms collect, report and even double-count sales from multiple sources, including those which might happen even if you didn’t run any activity. This means you are attributing to media spend sales that would have happened without media spend. This type of misattribution will mean you are using flawed data for budget optimisation and this in turn will lead to sub-optimal media performance. Misattribution makes your budget less efficient and less effective.

In order to detect incrementality we need to establish what would happen if your product or service didn’t have any marketing activity. There are three things – sometimes called “components” to look at here:

1. Trend – what is the underlying trend in your category an din your sales – are sales they in growth, decline or stable?
2. Seasonal cycles – What are the repeating patterns in the data – do sales increase or decrease in certain months, certain weeks on a regular predictable pattern?
3. Base brand equity – how many sales would you expect to see if you paused your marketing activity

These components can often account for more than 75% of your sales revenue. If your performance platforms are reporting 100 sales, it could be the case that 75 of these sales would have happened without any marketing activity. For many advertisers this is an “OMG” moment.

Imagine if you could identify the sales that would have happened without marketing or media support and then focus your marketing budget on activities that deliver genuine incremental growth rather than paying a platform “tax” for sales that were going to progress through your sales pipeline without any short-term marketing spend.

Let’s take a closer look at trend and seasonality and why it’s important. We’re going to use the “Bike Sales” dataset from Kaggle.

First let’s look at the sales data itself:

Here we can see bike sales from July 2017 to July 2022 over a total of 260 weeks.  We can make some initial observations. There is an underlying growth trend. We can also see that there are a number of peaks and troughs in the data. We see that the highest sales weeks are around 110k and the lowest sales weeks are around -30k so the weekly sales have a range of c. 140k.

Now let’s extract the trend component from the dataset:

We can see the underlying trend in the data, quantified using a moving average. We can see there is a strong upward trend from 50k sales to almost 85k sales.

Next, let’s extract the seasonality component from the data set:

It’s important to note here that “seasonality” doesn’t mean “seasons” as in Spring, Summer, Autumn and Winter. Here seasonality refers to any repeating cycles in the data. We can see there is  clear pattern of repeating cycles. These repeating cycles range from +10k to -20k.

And finally we are left with the Random component:

The Random component represents sales that are not explained by trend and seasonality. You can see that these random sales i.e. not explained by trend or seasonality, range from about +35k to -30k.

This random data is the data we test for contributions from media spend.  More on that model and its outputs in the next post.

The post What is incrementality in marketing – extracting trend, seasonality and brand equity first appeared on Marketing IQ.

Before we look at the 4Ps in detail let’s summarise the difference between strategy and tactics:

Strategy: Sets out which direction you have selected to achieve the macro marketing objectives your organisation has set. In marketing terms this might be to increase share by depositioning weaker competitors or to increase sales by increasing market penetration into new audiences. Think of strategy as the journey you need to make to get to your destination relative to everything else that is going on in the economy and in your category. Strategy is about the management of your resources in your business environment. Strategy is delivered over the medium to long term – it usually takes time to deliver, months and sometimes years. Strategy is what you’re going to do to achieve your objectives.

Tactics: Sets out the individual actions you will undertake in order to deliver the strategy. In marketing this might mean increasing revenue by increasing prices and using advertising to drive preference and reduce sensitivity to price.  Think of tactics as the individual decisions you have to take to complete your journey. Tactics can happen quickly – days, hours or even minutes.

Against this background the 4Ps are not exclusive to strategy or tactics, they can contribute to both. Let’s examine how each of the 4Ps works in a bit more detail.

P1 – Product

• What do we mean? Products have attributes which can confer advantage, or mean that the product lags behind market trends. If the product is ahead of demand trends, it should perform well in market. If it’s behind, it will do less well. The development of attributes is referred to as NPD – New Product Development – the more NPD generally means better, more competitive product and vice versa.
• Examples –
  • Apple used product technology to revolutionise the mobile phone market. Apple’s iPhone set totally new standards in mobile technology by combining a phone, a music player and a web browser, not to mention developing its associated app marketplace. Today Apple still retains around 24% of the mobile market.
  • Toyota led the way in hybrid auto technology development and retains the dominant share in this category.
• Timescale – All products (and most services) have to be researched, designed and tested before they can be launched. Product development generally takes time, it can be months and, in some cases, it can be years.
• Strategic or tactical? Such are the costs, resources and timescales required product development it has to be regarded as a strategic issue.

P2 – Price

• What do we mean? Price is what we pay for goods and services. There is no question that price can change consumer behaviour. As a general rule the lower the price of a good, the more units it will sell and vice versa. However, a high price can also be used to assert and reinforce superiority in a category. Discounts and sales promotions fall under the Price element of the 4 Ps.  These can be used tactically to change price for short time periods and increase sales for price sensitive goods and services.
• Examples –
  • Aldi commits to no frills value and prices itself as being seen as the lowest price supermarket.
  • John Lewis used to guarantee that they were “Never knowingly undersold”. Recently, this mantra was dropped. Since then, the company’s fortunes have changed suggesting this price promise had a positive impact on consumer behaviour.
  • Stella Artois is positioned as reassuringly expensive.
• Timescale – Price changes and promotions can be activated quickly, by day in retail and in real time in online / e-commerce environments. however, there can be longer term commitments to price vs category average. The Stella example shows a long-term commitment to upholding a price premium to position a brand. We could say that supporting a premium price is a longer-term initiative, reducing price is a short-term initiative.
• Strategic or tactical? Price reduction and discounting can be tactical in the short -erm but maintaining a long-term low or premium price relative to a category average usually requires a longer-term strategic commitment. In the case of Aldi, the whole business – from supply chain to checkout is structured around delivering a low-price, this is a long-term strategic initiative to secure a market specific position.

P3 – Place

• What does this mean? Place means Distribution. It’s where and how consumers are able to buy your product. For many years, distribution was simply about retail, but since commerce has migrated to online, distribution has now had an online manifestation. This could be the more generic impact of e-commerce such as wider access to product through much reduced impact of distance, but it’s also about how consumers assess distribution quality. Quality can be measured through speed of delivery, ability to try and buy and the returns policy.
• Examples –
  • Traditionally, retailers would sell more products if they increase their number of stores and vice versa.
  • Banks continued to close branches as more and more of their customers transition their banking activities from the counter to online.
  • Amazon revolutionised distribution by creating a massive and accessible e-commerce platform.
  • Apple revolutionised how music is distributed and bought.
  • ASOS revolutionised the distribution of multi brand clothing and fashion items.
  • Netflix has revolutionised how we consume movies – and had effectively killed off other physical formats such as DVD.
  • In the e-commerce world, delivery times, costs and returns policy all form part of the distribution characteristics of a company or brand.
• Strategic or Tactical? Traditional retail distribution networks are a strategic asset but they can be leveraged in a tactical way. They are strategic because they involve the use of a lot of capital and are slow moving. They can be leveraged tactically through localised incentives. Digital channels e.g. ecommerce are distribution channels but they are much more flexible and can therefore be used both strategically and tactically.
• Timescale – changes in traditional retail distribution are generally slow moving although the opening and closing of retail stores can have a significant impact on short term revenue. Changes in e-commerce distribution policy can have a quick effect. Increasing delivery costs or free delivery thresholds can have an immediate effect on consumer behaviour.

P4 – Promotion

• What do we mean? Promotion means marketing and advertising communications. In the marketing mix, promotion does not mean price promotion. Price promotion sits under the price element of the marketing mix. Long term commitment to advertising spend can confer competitive advantage and a long-term commitment to investing on a share of category spend (Share of Voice or SOV) that is greater than your market share (Share of Market or SOM) has been shown to drive growth.  This is called excess share of voice or eSOV. See a post on this topic here. Commitment to advertising consistently and at scale is a core component of consumer goods marketing where prices are generally low, decision making is as much emotional as it is rational and consumer purchase decisions are made quickly on System 1 ‘autopilot’ decision making. To enable this high mental availability is required, and that in turn requires always on advertising which is efficient at reaching mass or large segment markets.
• Examples –
  • Examples of large scale “always on” advertisers include Unilever, P&G, Sky, McDonalds and Tesco – these brands represent over £500m in adspend – seems a lot, but for these mass market brands, they are investing less than £10 per person per year to maintain high mental availability and high brand preference.
  • Of course, these brands are not representative and there is a long tail of advertisers who use much lower spends to deliver targeted communications to build online traffic, clicks, leads and sales.
• Strategic or Tactical? Clearly promotional communication activity can be both strategic and tactical. We talk about ‘brand building’ and we talk about ‘performance’ media. There is little doubt that strategic activity is about

The post What are the 4Ps of the Marketing Mix first appeared on Marketing IQ.

Attention metrics concern the degree of attention consumers give to different advertising media channels.  This is important if we accept that higher attention is likely to lead to higher cognition and memory retention. The value of attention isn’t universally agreed and the way attention converts to memory is a complex area [1]. If you take the view that advertising is consumed on a subliminal level, then the case for attention is possibly diminished. But if you believe that when information receives less attention, memory encoding decreases [2] then obviously attention is important. Either way, attention metrics are now firmly in the advertising and media planning Zeitgeist [3, 4] and there is no doubt that these metrics are going to be a big feature of media research, strategy and planning into 2023 and beyond. 

So, how do we address the issue of attention by media channel?

Lumen Research [5] have undertaken a study to estimate average dwell time as a proxy for attention to a range of channels.  Lumen’s findings are outlined below:

The formula being used by Lumen is % view x av. eyes-on dwell time x 1000 impressions. But in my view this formula could benefit from consideration of size of screen, distance from screen and clutter.

Let’s develop this further by estimating screen size and viewing distance ratio for each channel.

I have estimated screen sizes in feet so for a example, an average cinema screen is about 65 feet, an average TV screen about 3.5 feet (42″, diagonal) and the average PC or tablet size 1.2 feet (15″ diagonal). Mobile phone sizes are estimated at 3″ across. I have also added a metric for distance. Distances are also in feet with average distances from cinema seat at 50 feet, TV and BVOD at 10 feet, PC or Tablet at 1.25 feet and Mobile devices at 1 foot from the viewer. I have not included OOH as distances and screen sizes vary significantly – think tube cross track 6 sheet vs roadside 48 sheet. I have also excluded radio as size and distance metrics are not relevant. To create the size / distance ratio, size is divided by distance.

Adding clutter metrics to attention metrics

To add clutter metrics, I have used a scale of 1-5 where 1 is low clutter and 5 is high. Cinema, TV, VOD and BVOD advertising messages tend to be delivered sequentially so there is no surrounding clutter from a visual perspective. PC and mobile display advertising is often delivered in parallel and so tends to attract higher clutter. Mobile can have higher clutter and in some cases we see multiple ads, underlays and overlays being observed in the same content feeds – this can be seen in the example below [6], with two ads running simultaneously in a recipe page:

Combining these, we derive the the following size/ distance ratios and derive a clutter-weighted ratio by multiplying the size distance ratio by the clutter weighting metric (Ratio incl Clutter).

The Ratio including the clutter weighting can be graphed as below:

Cinema, given its dominant delivery scores highest, followed by full screen incline VOD, TV and BVOD within the range 1.30 to 0.35. Display PC activity ranges between 0.24 and 0.19. Mobile channels with their very small screen size and high clutter score in the 0.08 to 0.06 range. PC-based VOD scores highly when the screen size and closeness to screen are combined with the low clutter of an inline delivery.

Comments and adjustment suggestions welcome.

1. Interactions between attention and memory, Marvin M Chun and Nicholas B Turk-Browne, Science Direct 2007 https://ntblab.yale.edu/wp-content/uploads/2015/01/Chun_CONB_2007.pdf
2. Memory and Attention Long, Kuhl, and Chun in Stevens’ Handbook of Experimental Psychology and Cognitive Neuroscience (pp.1-37)
3. What are attention metrics and why are they crucial for digital advertising? Mateusz Jędrocha, The Drum, August 25, 2022 https://www.thedrum.com/profile/rtb-house/news/what-are-attention-metrics-and-why-are-they-crucial-for-digital-advertising
4. No Longer a Novelty, Attention Metrics are Now Fully Ingrained in Agencies’ Planning and Measurement, Tim Cross VideoWeek, 21 July, 2022https://videoweek.com/2022/07/21/no-longer-a-novelty-attention-metrics-are-now-fully-ingrained-in-agencies-planning-and-measurement/
5. Lumen Research, “Media Buying” https://lumen-research.com/media-buying/
6. Bread in four easy steps, BBC Good Food, https://www.bbcgoodfood.com/recipes/bread-four-easy-steps, retrieved 12 June 2024

The post Towards Attention Metrics by Media Channel first appeared on Marketing IQ.

ESOV was originally identified by John Philip Jones a hybrid marketing practitioner-academic who looked at a number of relationships between marketing and media investment and sales responses.

Here’s how eSOV works. If you have a 10% share of market (SOM=market share) and a 12% share of voice (SOV=share of category adspend) then your eSOV is +2. Jones was able to estimate the statistical relationship between eSOV and sales using panel data.

This relationship has been used by marketing planners for around twenty-five years. It’s a relatively easy concept to grasp, communicate and evidence with data. Most importantly, it’s a marketing argument that many boards are prepared to give a hearing and accept.

In recent years the marketing effectiveness specialists Les Binet and Peter Field have re-examined this relationship and added some interesting findings about how the eSOV concept is impacted by creativity.

But, as with many marketing concepts, there is some devil in the detail. There are five big points that are often overlooked but which should still be considered as part of the marketing planning and budgeting processes.

• First – not all categories and advertisers behave in the same way when it comes to eSOV.
• Second – SOV and SOM calculations often exclude companies than don’t advertise – think Google, Facebook or Tesla – brands that grew with little advertising support in their early years. They gained share of market through product advantage.
• Third – eSOV tends to work much better when the excess share of voice is carrying award-winning creative work and vice versa.
• Fourth – you need to think about the relationship between the required SOV and the impact on profits.
• Fifth – Jones recommends using econometrics to fully understand how eSOV works as a component driver in your marketing mix. SOV or eSOV may not be the only explanatory variables in your mix. You will need to understand the contribution of all drivers to make valid statements about eSOV.

The post Does excess share of voice (eSOV) guarantee brand sales growth? first appeared on Marketing IQ.

These non-linear effects are normally grouped into two areas:

1. the delayed effect of advertising and
2.  diminishing returns in advertising.

Let’s look at each one in turn:

1 – Adstock or Carryover

The first type of non-linear effect we see in media investment is the carryover effect. When we advertise, we know that the effects are not always seen immediately. This is because advertising, well good advertising, gets remembered and the memory effect on consumer behaviour may be felt some time after the ad is seen.

So, for example if an advertiser buys 100 GRPs in a week, the full effects of that investment are not confined to that week. What happens in practice is that the effect of that advertising tends to “carryover” into the next week and the week after that. How do we know this? We know because when we build models (e.g. MMM) to quantify response to media investment, they tend to be much more accurate when we carry-over the effect of advertising into the following weeks.  We call this carryover effect Adstock.

You might ask “how much do we carry over?” The answer to this is found by testing different Adstock carry-over levels and analysing how they correlate with sales response over time.  The most commonly used analogy here is borrowed from nuclear physics (don’t worry it’s not as complicated as it sounds). In nuclear physics radioactive substances have a half-life, that’s the time it takes for their radioactivity to decay by exactly half.  Marketers borrow this thinking and use half-life decay rates to model lagged advertising effects. We refer to the length of time required for advertising Adstock to fall by half as the ‘half-life’.

So, as an example, if in week 1, 100 GRPs create 1000 sales, a one week half-life might see that effect carry-over to 500 sales in the second week, 250 sales in the third week and 125 sales in the fourth week.    Any model that counts only the 1000 sales in the first week underestimates the lagged ROI of those first 100 GRPs. That’s because over the four weeks those 100 GRPs delivered 1,875 sales (1000+500+250+125) rather than the 1,000 sales originally reported. We can see that by considering Adstock, the ROI of the first week’s 100 GRPs almost doubles.

2  – Diminishing Returns

The second type of non-linear effect we see in media investment is diminishing returns. The law of diminishing returns states that as more of something is bought, the less utility is gained from it.   A frequently quoted example is agriculture – as more resources are invested into an acre of land, the yield of corn does not increase proportionally.  A more day to day example I like to use is buying coffee. The first coffee of the day is wonderful and hugely satisfying. The second is less satisfying and by the time I venture to more than three cups I’m not getting much satisfaction at all. These are both examples of diminishing returns and the same patterns can be seen in media investment.

Let’s assume we are investing in media to drive web traffic. If we buy 100 GRPs in a week we might see 100,000 visits.  But if we invest in an additional 100 GRPs in the same week we might see these incremental GRPs deliver only 50k visits. And if we invest in a further 100 GRPs in the same week we might only see 25k additional visits generated. We can see the visits we are generating fall by half for every 100 incremental GRPs we buy. This is a diminishing return and it applies to all channels from TV to PPC.

What’s the cost of this diminishing return? Given that 100 GRPs might cost £350k we can see how  taking the spend over a certain level in a specific time frame starts to reduce ROI significantly.   Whereas the first 100 GRPs generated 100,000 visits, 300 GRPs only generated 175,000 visits (100k+50k+25k). Our CPV has increased four times from £3.50 on the first 100 GRPs to £14.00 on the third 100 GRPs. When we apply these examples to large scale media budgets, we can see how diminishing returns can have a dramatic effect on media effectiveness. In the worst case scenarios budgets are set at levels so high that they risk producing no additional sales response at all.

What causes diminishing returns?  Diminishing returns are usually caused by market size constraints. If a brand has a consideration pool size of 5m consumers, with ten percent actively in market in a week or  a month, over-spending excessively against this group will not change purchase behaviour sufficiently enough to match your increased spend, you will simply spend more, sales will not grow at a proportionate rate and your media ROI will fall.

What does this mean for media planning and investment?

The challenge for media planners is to arrange media investment to leverage the carry-over effects produced by Adstock whilst reducing the impact of diminishing returns.

The main implications for media planning are around setting budget weights and phasing to leverage these two effects to maximise media effectiveness. Budget weights have to be contained within acceptable diminishing return limits while Adstock carry-overs can be used to fill gaps in a pulsing media strategy.

Further reading

Broadbent, S. (1979) “One Way TV Advertisements Work”, Journal of the Market Research Society Vol. 23 no.3

Joy Joseph, 2006, “Understanding Advertising Adstock Transformations” (independent)

Fry, T.R.L., Broadbent, S. and Dixon, J.M. (2000), “Estimating Advertising Half-life and the Data Interval Bias”, Journal of Targeting, Measurement & Analysis in Marketing, 8, 314-334

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The post Adstock and Diminishing Returns: non-linear advertising effects first appeared on Marketing IQ.

1. Have a pitch lead. Before we get into any tips it’s important to have a pitch lead. This is the person who pulls the story of the pitch together. This person needs certain qualities; they need to be able to synthesise multiple sources of information into a single coherent and accessible story. Pitches generate huge amounts of information but whilst a lot may be useful in defining the overall approach, not all of it is required in the pitch story. Leading the pitch requires sifting the wheat from the chaff and developing a logical, well argued, simple and persuasive narrative.
2. Answer the question. This may seem simple and obvious but it doesn’t always happen. The temptation for agencies is to reframe the question to suit their strengths. This is like answering an A level question with everything you know about a topic, rather than specifically answering the question asked. Do you remember what teachers used to say, “make sure you answer the question”? Moreover, when you receive a brief you are receiving a document that will have been drafted, edited, circulated, amended, updated and agreed by various client-side stakeholders. The questions in the brief are the questions that everyone in the client team wants answered. Do them the courtesy of answering those questions. There are rare occasions when the brief isn’t what the client wants. This is counter-productive and unhelpful. If you think this might be the case try to flush it out early in the pitch process and ask the client pertinent questions.
3. Have a simple compelling narrative. You must have a pitch story that provides the narrative backbone of everything you cover in the pitch. If you think about most movies or novels that have made an impact on you, they will have a story and the story will be based on one of nine main plot themes – rags to riches, quest, tragedy or rebirth. For most pitches the story will be either rags to riches or rebirth. Think about how you can corral your insight and strategy, delivery and results into one of the these plots. You must be able to write the outline on one page – if you can do these things, thenyou could have the makings of a compelling story.
4. Talk about the client, not yourself. It’s always interested me that the word “you” was the word most often used in Beatles song titles. Clients and prospects want you to talk about them and how you can change their world. When you talk about your agency it must be in the context of what you can do for the client. Use a sense check here; if when you talk about you agency it’s not explaining the relevance to the client, think again.
5. Be different. From the moment you submit your RFI or walk into the pitch room the client wants something that not many people have. They are looking for original high value thinking. Dare to be different, shine new light through old windows, make your case logically, provide the commercial benefits. You should be leaving the clients thinking you were bold, different and exciting. If it was too bold they can ask you to dial it down but if you aren’t bold, there’s no way to dial it up after the event.
6. Don’t use generic material. The scourge of pitches. Why? Because it’s so obviously a substitute for either work or knowledge or worse, both. Ultimately, it shows that the agency doesn’t know how to be different. Who wants to work with any agency that relies on generic industry research or case study material to make its case? You can use the findings of such research but you must apply it directly to the context of the client you are pitching for.
7. Generate your own insight. So this wins pitches be in no doubt. New, unique, different and high value insight tells clients something they don’t know. It makes them think hard about what you are saying and who is saying it. It builds an intellectual bond. Even if you are slightly wrong you gain huge points for making the effort to produce something new and different. If possible, give the client a taster of your insight at chemistry – if your work is good enough it will make putting you through to the next stage irresistible.
8. Define the strategic problem in a “business school” way. The communication problem in the brief will sit within a wider set of issues affecting your client – a growing or declining category, increasing new entrants, low entry barriers, increased price competition, vulnerability to alternative suppliers and so on. You will need to understand this context to answer the brief correctly. This thinking is often absent in pitches but it shows the client that you understand their category as well as the their consumers.
9. Have a big idea. David Ogilvy once said ‘a campaign that doesn’t contain a big idea will pass like a ship in the night’. At the time he was talking about creative ideas. But with the media landscape as complex as it is today, a big idea can be a powerful antidote to media complexity. That idea should be something that works across multiple platforms and provides multiple communication benefits to the client. It should be an idea – not necessarily an individual media property – that the client, agency and consumer can all coalesce around. The idea should bond like DNA.
10. Be careful with tools and tech. Every top 20 agency has lots of tools and tech. Some of these are the result of massive investment. Some are just nice front ends to simple spreadsheets. The issue for clients is they don’t know the good from the bad and the useful from the useless. Tools and tech are potentially valuable but clients can’t always evaluate them well enough to inform a pitch decision. As a result these issues are often taken out of their decision making process – either consciously or subconsciously. If you are going to talk about tools and tech make sure they can be understood and the benefits are clear and relatable for the clients.
11. Bring it to life. Where possible use mock ups to show how your campaign might look when it does live. This isn’t always easy but it makes your plans much more buyable. There are some great free tools that can help here – for example
12. Use proof points. When you make your points, whether it’s about the brand, category, consumers or customers, try to conclude the points with evidence.
13. Demonstrate your ROI case. When you are pitching, you are pitching to spend someone else’s money. It could be shareholders’ or it could be seed investors’ or private individuals’ money. Money is at the heart of pitch decision making. Make sure you demonstrate how you will buy media and invest media money optimally. If you don’t cover this you are leaving a big hole in your case.
14. Take a position on fraud and tech stack costs. This is a big issue for clients and it’s not made any easier when ISBA and PwC tell them 50% of their digital media money doesn’t get in front of consumers and 15% of it “disappears into a black hole”. Many tech costs make the digital performance results better but you will need to explain how yours do this – in a simple and clear way.
15. Field good people. All agencies have different types of people. In a pitch situation you need to field the people who convey knowledge, experience, logical thinking and confidence. The client doesn’t want their budget to be the guinea pig for the graduate training scheme. This doesn’t mean you have to field senior management but it does mean you have to field really good “day to day” people. The people who will be working for the client.
16. Tell a story that will resonate with your prospect. Media is complex and a cleat pitch story provides a spine around which detail can be discussed. Tell them how you are going to take them from A to B and include details at relevant signposts along this process journey. Provide this navigation so that if they are momentarily distracted they can reengage quickly and not lose key threads for the rest of the meeting.
17. Show the prospect where they will fit into your business. If you are pitching a £5m client and your agency billings are £200m they will be 2.5% of your business. This means you will have to demonstrate why they will be important and how you will prioritise and service them if they sign up with your agency.
18. Don’t ask too many pre-pitch questions. Many agencies think these questions are a useful way to build a relationship with the client. Most of the time these questions are an irritation for the the client; they’ve decided to run the pitch, they’ve worked internally to create the brief and pitch document. They given you the problem. They now want you to go and solve it.
19. Pitch in a room with a good aspect. This is a strange one, but it can matter. Rooms that don’t have natural light can contribute to a negative vibe. You don’t have to go grandiose but do pitch in a room that clients would want to be in again. Make the room interesting.
20. Last but not least, food. Serve some memorable snacks or lunch but avoid things laced with sugar. It causes tiredness and distraction. You need to serve tasty low calorie food. Serve something memorable; this may sound frivolous but it’s a way of driving recall. After two days in meetings the client may forget it was your agency that made a key point. But if the client says “that was the agency that served the organic chicken skewers” someone will remember that was you.

The post How to win a media pitch first appeared on Marketing IQ.

On April 7th, Mark Woolhouse Professor of Infectious Disease Epidemiology at the University of Edinburgh said ‘As things stand we could be out by a factor or 10 or even 100‘ [1].

Testing only those admitted to hospitals with symptoms provides a small, biased and unreliable sample which in normal circumstances would not be considered of any use at all. As a result, we have no idea about how many people have actually been infected or recovered or what its true mortality rate is.

Estimates of the number of cases currently range from the government’s official 191,000 (to 5th May) to a possible high of more than 23m – based on 800 cases for each of the 28.7k confirmed deaths. The difference between 191k and 23m is a factor of 120 i.e. close to Mark Woolhouse’s inaccuracy factor of 100.

The range between these two numbers is important because it includes two very different scenarios. Either Coronavirus is much less contagious than we thought, with a high mortality rate or it is far more infections than we thought, but with a much lower mortality rate.

In the first scenario there is a case for lockdown, because it looks like it’s keeping the number of cases under control. But in the second scenario it looks like 50% of the population have had the virus and the lockdown was too late. If we are at 50% we are closer to herd immunity levels which reduce the need for a strict lockdown.

If we can get to some accurate measurement we will be able to:

1. Know how many people have actually had the disease in the past which provides us with a framework to calculate true infection, recovery and mortality rates, all of which are currently wrong.
2. Understand more about the pattern of infection and by using reproduction rate (r rate) in scenario planning we would be able to establish a clearer picture about how this pandemic might evolve in the coming weeks.
3. Estimate whether we are coming close to herd immunity – right now, this remains the only practical weapon against this disease until we have a vaccine – but we have no idea about how close we are to this stage. Understanding levels of herd immunity will be one of the keys to ending the lockdown.
4. Understand the geographical distribution of the disease which may in turn help us identify whether different regions and communities are affected in different ways, thereby allowing us to target resources more accurately.

What should the government have done / do next time?

Accurate sampling was the big miss. A huge miss in fact. The government picked a sample that by its own definition is not representative. The sample contains glaring errors so bad as to render it effectively useless. But we could have got the sampling right. We could have gathered vital data through sampling the population for both reported symptoms and actual test results by:

1. Building a nationally representative sample for symptom for self-reporting without testing. This disease has a number of known symptoms that can be reported online. Even if these don’t amount to a diagnosis they will help understand how the virus might be spreading. Mobile devices make collecting this data easy as has been shown by the COVID-19 project run by King’s College London.
2. Creating a nationally representative sample for weekly testing. A UK nationally representative sample only needs to be about 1k individuals. If tests cost £100 each this this would cost around £100k per week.
3. Running anonymous secondary Coronavirus tests on hospital blood samples collected for other reasons.

How do these data help end lockdown?

These simple forms of sample measurement would allow us to understand total numbers much more accurately, we would know how many people have had the infection and how many have survived. From this we could establish true recovery and mortality rates. Through continuous weekly sampling would be able to establish patterns of infection and evidence of any second or subsequent waves. Armed with this information we would be able to stop guessing about the end of lockdown and put in place policies based on accurate evidence.

Without accurate case measurement it is extremely difficult, if not impossible, to build an effective strategy to deal with the current situation and make plans for ending the lockdown. Without accurate measurement we are left guessing and we are building policy on guesswork.

Update 11th May 2020

Sir David Spiegelhalter, one of the worlds leading statisticians and professor of public understanding at the University of Cambridge has accused the government of an extraordinary failure to prioritise randomised testing – the type testing highlighted in this post [2].

1. Daily Telegraph Online ‘Why the Coronavirus tests you’ve never heard of hold the key to exit from Lockdown’ 7 April 2020.

2. The Times ‘Risk expert lambasts number 10 for failing to prioritise randomised testing’ 11 May 2020

The post Coronavirus: why measurement is the key to ending the lockdown first appeared on Marketing IQ.

Whilst this may appear counterintuitive to many companies, and particularly to CFOs, the reasons for Unilever’s move are commercially logical. So, let’s explore why this marketing powerhouse has made this commitment to spend through any downturn.

First Unilever knows that now is the time to take advantage of historically low media rates

Currently audiences are up around 40% and media rates are down by about 40%. This means media markets are currently presenting marketers with exceptional value and a chance to build brand equity quickly and cheaply.

But before we talk about media value, let’s spend a moment on AdStock. ‘AdStock’ is arguably the most important word in marketing investment yet many marketers outside the P&Gs and Unilevers either aren’t aware of it or don’t fully understand it.

AdStock is the carry over effect of an advertising campaign. A 90% TV AdStock means 90% of your awareness will carry over into the next week and 90% of that into the following week and so on in a slowly decaying pattern. But here’s the clincher; a GRP or awareness impact of 100 with a decay rate of 10% per week requires 43 weeks to fall to 1. So investing in GRPs now means you are buying futures in brand awareness for up to 43 weeks ahead – at a heavily discounted price. And what’s really interesting about these AdStock futures is that unlike financial futures, they are risk free. Unilever know that this stock of advertising reach, awareness and brand preference will continue to pay dividends over the next few months.

So, whilst Unilever is cutting back on production it looks like it’s committed to taking advantage of the current preferential rates in media markets.

Second, Unilever will know that recessions and downturns can increase consumer use of lower price products – and change perceptions of own label positively

The big danger for premium brands is that consumers switch to lower priced own-label brands during any downturn.

Following the 2007 recession, McKinsey found that 18% of consumers switched to lower priced brands [1]. Whilst brand owners might expect consumers to switch back to high price products when the recession ends, the experience of buying lower priced products means consumer attitudes to lower priced brands can change – in favour of own label. McKinsey’s research found that of the consumers who had trialled lower price brands, 46% said they had performed better than expected and more worryingly for premium brands, 34% said they no longer preferred higher priced products.

Unilever will know that they have to counter this effect to protect market share in the future.

Third, Unilever knows that category brand positions can adjust and change in times of crisis.

Category brand positions are more likely to change in a recession than in times of relative stability.

In 2009 Domino’s was not the most popular pizza in the US. When the recession started to bite Domino’s invested in new recipes, research and advertising. The result was that Domino’s was catapulted into the top of the category. Earlier, in the 1991 recession Pizza Hut and Taco Bell took advantage of McDonald’s decision to drop its advertising and promotion budget. As a result, Pizza Hut increased sales by 61%, Taco Bell sales grew by 40% while McDonald’s sales declined by 28% [2]. In the 1970s oil crisis Toyota decided to continue advertising support for its cars whilst Honda and Nissan cut back. The effect of this move was not only to push Toyota’s sales ahead of its Japanese rivals in the US but it also nudged Toyota ahead of VW. By 1976, Toyota was the US’s leading imported car brand.

Even earlier than that, immediately prior to the great American depression the leading cereal brand was Post. You know, that cereal brand you’ve never heard of. Before the recession Post was a strong brand. It also had a smaller competitor called Kellogg’s.

Just before the 1929 crash, founder Will Kellogg had all the plans and copy for Kellogg’s advertising in 1930 prepared. In the autumn of 1929 Kellogg went on holiday but received a call from company president Lewis Brown recommending that ad budgets cancelled because of the stock market crash. Kellogg’s response was “I don’t think we’ll cancel our advertising now. In fact we might even increase it”. Kellogg’s earnings for 1929, 1930 and 1931 set new records [3].

But more than this, the category was redefined by Kelloggs’ action and Post’s inaction for almost 100 years and still counting.

And fourth, Unilever marketers will know that if you’re not in the market when recovery comes, it’s going to take longer to regain lost ground.

As tempting as it may be to go quiet, current media deflation means there will inevitably be high media inflation in the near future.

Media owners will want to end the year with as little damage as possible. If they’re down 30 in April and May they will be looking to claw as much of that back as they can when demand returns – that means they will harden their pricing in the next two quarters. Those advertisers who stayed in the market will have a stronger negotiation position – whilst those who stayed out could be punished from a commercial perspective.

Summary

According to research by Bain, ‘playing offense almost always trumps hunkering down or weathering through’. And more than this, Bain’s research showed that ‘winners in a downturn make more dramatic gains than winners do during boom times [4].

When we look at advertising and marketing we can see that marketers are living in a times of risk, but they are also living times of opportunity; the opportunity to get ahead faster than during boom times. And from a brand communications perspective, the current unique situation provides opportunities to build and strengthen brand position through growing audiences, falling media rates and dynamic category structures. Coronavirus it seems is presenting us with threats and opportunities at the same time.

1. McKinsey ‘How the recession has changed US consumer behaviour’ December 2009
2. Forbes.com ‘When a recession comes don’t stop advertising’ September 2019
3. History of the Kellogg Company (unpublished) 1948, quoted from Simon Broadbent ‘The advertising budget’ NTC 1989
4. Bain & Co ‘Using the next recession to change the game’ October 2018.

The post Unilever points the way by maintaining adspend in Coronavirus crisis first appeared on Marketing IQ.

You also know that there is a small seasonal factor because this is a month when you expect a modest rise in traffic – but not this much. At the same time the trading team have made some downward adjustments to your product pricing. One large competitor has also launched a new TV and cinema campaign.

You suspect that some or maybe all of these factors have increased your traffic, but which ones, and to what degree?

Enter full funnel attribution:

Full funnel attribution ditches both conventional linear measurement and simple attribution models (first, last, even etc). Instead, full funnel attribution (sometimes called Multi Touch Attribution) uses statistical technique to detect explanatory patterns between driver variables (e.g. spend in different channels) and response data.

This channel agnostic analysis is of immense value to marketers. Why? Because it is only by analysing these patterns across the entire funnel that marketers can get an integrated view of how their marketing really works.

Enter statistical relationships:

Statistical modelling lies at the heart of this type of attribution analysis. Analysts use techniques like linear, logistic and multiple regression to identify and quantify relationships between variables like spend in different channels and their impact on response variables, usually total sales. Rather than looking at the last touch, these techniques allow marketers to identify the channels and spend weights that drive traffic into the mid and lower funnel. Statistics are agnostic; they reveal the true patterns and relationships within the data. This enables marketers to make much more reliable decisions about optimising media investment.

Enter independent and dependent variables, x and y.

These statistical relationships are called predictive relationships because they explain – and predict – how one dependent variable (y) changes as another independent variable (x) changes. The variable we are predicting is the dependent variable because its movement is dependent on the movement of the independent variables. For example we may be interested in understand how sales rise as a result of increasing advertising spend. The dependent variable (here, sales) is always called “y”.

The independent variable (here, advertising spend) is always called “x”. We may have several independent variables in which case they are called x1, x2, x3 etc.

When we quantify the relationship between advertising and sales, we might find:

• For every £1k we spend on advertising (x1) this channel delivers 100 sales (y)
• For every £1 we increase our prices (x2), we lose 1,000 sales (y)
• For every £1k our competitors spend (x3) we lose 50 sales (y).

Enter controlling variables:

Control variables take account of other factors in the mix that could be affecting your model. Examples of controlling variables are price, distribution, seasonality and competitor spend. If you’re not controlling for all the x variables potentially affecting your sales, any findings are likely to be inaccurate. Only when you have statistically controlled the effect of other variables can you make any statements about ROI from any one channel.

Enter AdStock:

AdStock concerns the measurement of the delayed effect of advertising. AdStock is one of the most influential yet least understood concepts in advertising. It has a scientific pedigree and has been proven and reprove in multiple studies. Typically, with TV this is around 10% decay per week. If a campaign generates an advertising awareness of 50% a 10% decay rate means this 50% ad awareness would require more than 30 weeks to decay to 1%. During this time AdStock contributes to driving sales, many of which are misattributed to other lower funnel channels. Most short term measures do not consider AdStock but it’s effect is almost always present and powerful, particularly for larger advertisers.

Enter the baseline:

It’s also critical for marketing and media planning to know where your base is. The base is the number of sales you would generate without marketing activity. Technically it’s where your sales cross the (y) axis when all your x values are zero. When we talk about long and short term effects the short term is generally effects that are incremental to the base while long term effects build the base itself.

How do we know if our model is accurate?

Modelling provides a number of diagnostic tests which indicate how relatively the model and its outputs are. R2 is the best-known indicator of model accuracy it is not the only indicator or the most reliable.

Enter T tests and P values:

The t test and p value important diagnostic tests to help us understand how reliable our model is.

Model coefficients are always reported with an error and the t test is the coefficient divided by its standard error. Clearly we want this number to be high because that indicates the error is low ie it can be divided into the coefficient many times. If the t value is low (ie the error can’t be divided into the coefficient many times) the. the model findings are inaccurate.

The p value indicates the probability that the null hypothesis is valid i.e. that there is no relationship between the variables e.g. spend and sales. In layman’s terms is the probability that our model is wrong. So, want the p value to be low. The popular cut off for p values is anything over 0.05 indicates the model is inaccurate.

Enter actual vs fitted forecasts:

When we have built our model we can compare what our model forecasts to what actually happened. This helps see how well the model predicts the past and indicates how well it might predict the future.

Actionable outputs

Of course all analysis is relatively unhelpful unless we can provide actionable outputs. So, here’s a list of what we should be looking for to help improve how marketing works in a practical sense:

1. Our base: This is important – it’s the number of sales we expect to see if we don’t do any marketing. Marketing existing to deliver incremental sales in the short term and grow the base (sales that are not attributable to any one channel – basically, brand equity).
2. The impact of price: Price is an important determinant of sales. If our price is too high it will have a negative effect on sales. We must know what that effect is.
3. The impact of each independent variable on sales: These are the marketing levers we can pull. The more of x we invest, the more our sales (y) will grow.
4. Diminishing returns: Our model will produce a response curve for each channel. As we invest more the rate of ROI return will decrease. It will reach a point where no more sales will be generated from increased spend. It’s essential to know where that point is to avoid budget wastage.
5. The impact of carryover, sometimes called AdStock, the delayed effect of past adverting or future awareness and sales.

With all this insight available it is possible to forecast what might happen when your investments are organised in different ways. This scenario planning allows marketers to explore a range of investment scenarios to identify the plan that is:

1. Most likely to deliver the volumes of sales they seek
2. At the price that works for the business
3. At a cost per sale that is economically viable.

The post What is full funnel attribution in marketing? first appeared on Marketing IQ.

So why are we talking about media planning again, what does it really mean and why is it set to become more important?

The media landscape has changed almost beyond recognition in the last fifteen years. Since Google became mainstream around 2005, we have seen huge growth in digital media consumption and corresponding growth in digital media budgets. Because of its high measurability and its proximity to the purchase, there has been increased focus on using digital media to convert consumer demand into purchases.

But there is a critical distinction to be made between channels that convert demand and channels that create and grow demand. Whilst lower funnel channels convert pre-existing demand, mid and upper funnel channels deliver the brand preference that is essential to create and grow brand demand.

Many of the world’s biggest digital businesses recognise the ability of traditional media to deliver growth at scale; Amazon, Booking.com, eBay, Facebook, Google, HomeAway, Hotels.com and Microsoft are all huge users of traditional media and especially TV.

LinkedIn Case Study

A good example of a pure play digital brand using traditional media to grow is the recent campaign activity from LinkedIn.

Across 2019 it has continued to invest in offline media at scale – utilising print media – especially newspapers and outdoor.

Example LinkedIn tube ad October 2019

So why, given the perfect target audience reach of LinkedIn, and its own heavily used subscriber platform why would it wish to communicate in traditional media?

There are four key reasons for this:

First, consumers still spend a lot of time in environments where offline media will reach and influence them. They spend almost 3 hours per day watching TV. The reach of outdoor advertising remains undiminished, and the gradually declining medium of press still reaches over 11m adults every day in the U.K. (Newsbrands 2019). This ability deliver high scale reach, physical presence and mental availability is vitally important to the health of brands (see Sharp, How Brands Grow).

Second, these channels deliver strong visual or aural impact; it’s difficult to ignore or “Adblock” TV, press, radio or outdoor. This cut-through presence helps marketers communicate key aspects of brand personality quickly and effectively and drives memory building in consumers’ minds.

Thirdly, communicating in paid channels confers brand status, authenticity and trust – increasingly important characteristics in the current low-trust media environment of fraud and fake news.

And last but not least, traditional media is low cost on a CPM basis – TV, print, outdoor and radio all have CPMs that are typically below the CPMs you might see in search engines.

These four points are some of the reasons why the world’s largest digital superbrands still pile billions of pounds or dollars into traditional media channels.

So what is the craft of media planning?

The most effective campaigns combine both mass, segment and individual communications across both digital performance and high reach traditional media. But making investments across these multiple channels requires deep levels of audience insight combined with high levels of media knowledge plus experience in planning and evaluating all media channels and the experience of knowing how to orchestrate the selected channels into a single cohesive plan. And deploying this skillset is what we call media planning.

The craft of media planning is knowing how to use media to grow demand for brands rather than simply harvesting sales from within the current demand pool.

The toolkit required to use media to grow brand demand has the following component parts:

1. Understanding the business, marketing and campaign objectives of the brand
2. Understanding how the consumer sees the brand and relate to it, what they like about it and why they buy it.
3. Understanding the relative position of the brand in the category and how it is different from competitors
4. Understanding the purchase and usage patterns of the brand
5. Understanding how the category behaves – from seasonality to competition
6. Knowing all the different types of data and research that will help build understanding of consumer behaviour and media channel performance
7. Understanding which audiences, segments, behaviours, regions, towns, cities or postcodes are most likely to yield the target audience being sought.
8. Having a strong understanding of how all media media channels work, their cost structures and the type of business outcomes they can deliver
9. Having a strong understanding of the communications task capabilities of each channel – do they build awareness, increase consideration or drive sales conversions?
10. Having an understanding of how media channels can synergise to identify where different combinations can have a 2+2=5 effect
11. Understanding how media channels can be used creatively to engage consumers
12. Knowing how media channels are sold, bought, traded and managed
13. Be able to identify and define the type of campaign that is likely to deliver the marketing and campaign objectives most effectively and efficiently
14. Being able to organise the audience insights and media channel capabilities and costs into a cohesive plan of action which details of what each channel will contribute, how channels will be used, and how they will be measured and controlled.

Is media planning art, science or craft?

Producing an effective media plan is not an art and it’s not a science. But – it has the characteristics of both; good media planning requires logical data analysis and it also requires intuitive and innovative thinking.

The best media planners serve a professional apprenticeship followed up by practical experience – learning through experience – which makes media planning a craft.

So why do we need the craft of media planning more now than ever before?

Fifteen years ago everything looked like it was going to go digital. And it also looked like traditional media was going to decline terminally. But the reality is neither have happened. Yes, digital has grown enormously but it hasn’t moved so far up the marketing funnel as to displace traditional media – if anything digital has hovered around the lower funnel zone. Meanwhile, traditional media has declined but it still completely dominates the upper funnel.

All this means planning consumer and B2B communications has got a whole lot more complicated. Advertisers need specialists who can navigate through this complexity on their behalf, find the opportunities and produce integrated plans to deliver business objectives and commercial outcomes.

In short, the need for high quality media planning has never been greater or more pressing than it is now.

The post What is the craft of media planning? first appeared on Marketing IQ.