Detailed methodology

Advertising spend data

For this analysis we have used a combination of Nielsen and Standard Media Index. SMI is based on actual media spend from booking data covering 65% of UK media agency billings. The data covers all above the line media. Importantly, it provides a detailed breakdown of digital spend across display, video and paid search. So, for newsbrands, it covers spend both in print and in digital.

In order to get figures as close to real world adspend levels as possible, we’ve applied a simple formula. We’ve taken offline adspend figures from Nielsen and used SMI digital adspend percentages. By combining these two pieces of data, we can fill in the gaps in each; so we calculate the percentage of total spend taken up by the Nielsen offline spend figures and also calculate total digital adspend figures, giving us an accurate proportion of the total media landscape.


Total adspend – how it’s calculated

Categories and super-categories

This study is designed to provide maximum benefit and the widest possible application. Benchmarketing have introduced an amazing innovation to make this happen. Looking at 30 individual categories, analysing characteristics such as purchase behaviour as well as how they behaved in relation to response to advertising investment, Benchmarketing developed five ‘super- categories’ as distinct segments. Although the products in the categories may seem quite different on the face of it, we know that consumers think about and approach them in similar ways. And importantly, the response to advertising follows the same pattern.

These categories cover an impressive 86% of the total UK advertising market. This equates to over 90% of advertised brands (some categories, such as pharmaceuticals, don’t advertise in the UK). This overcomes the issue of having enough cases in a sector to enable robust and actionable conclusions. In addition to the super-categories, there are also enough cases for robust analysis in four individual categories – motors, finance, supermarkets and retail. As a result of this work, the vast majority of UK advertisers will be able to determine optimal spend in newsbrands.


The five super-categories


Frequent, habit driven purchases. Brands are generally favoured by default rather than thought. Low cost

Choice is often welcomed and purchases are more considered, providing valued moments of ‘me time’ or family time. Purchased relatively frequently at low- medium value

Goods and services that are bought weekly (more or less). Medium brand consideration and medium value

Goods and services mostly purchased or reviewed on an ad-hoc basis, the use of which often bring enjoyment. Quite high brand consideration and medium value

Purchased roughly annually (sometimes more, sometimes much less). Varying degrees of interest but often significant spend and therefore often highly researched

Examples – confectionery & sweets, household supplies, media e.g. newspapers or magazines

Examples – restaurants & coffee shops, drink – non- alcoholic FMCG like fizzy drinks, food FMCG, charities, beauty & personal care FMCG, health & medical FMCG, pharmaceuticals (not an advertised category in the UK)

Examples – alcoholic FMCG, gambling, National Lottery, entertainment & leisure, supermarkets

Examples – computers & software, toys, games & consoles, clothing & accessories, consumer electronics, telecoms, retail (non-grocery)

Examples – government and public sector, insurance, other offline services, other online services, travel & transport, energy & utilities, business services, motors, finance BSILC (banking, savings, investments, loans, cards)


Profit return on investment (PROI) analysis

To focus on PROI, Benchmarketing have concentrated on splitting the cases within each campaign into three spend ‘tertiles’; low spend, medium spend and high spend (one third of the overall cases in each). Once this is complete, an analysis of the PROI of different levels of print and digital newsbrand spend is made. Using this data enables us to see the effects of different levels of print and digital newsbrand usage on the overall profit of advertising campaigns. This allows us to make credible, evidenced spend recommendations.


A meta-analysis of econometric models

Econometric analysis consists of identifying and assigning a weight to the various elements driving sales, such as advertising, PR, pricing, product range, competitor activity and brand awareness. Benchmarketing conducted a meta- analysis of 684 econometric models from 2011-2017, across a number of different sectors. Meta-analysis is the interrogation of multiple sets of results data – “metadata”. It is common in pharmaceuticals, particularly in clinical drugs trials.

One trial isn’t enough, you need hundreds to be sure of your results. Then the key skill lies in diagnosing why results between groups are different. In this work, the metadata comes from a single line for each model, with the inputs (spend, media mix) and outcomes (return on investment) all quantified consistently between models, together with the category of the brand being analysed.

Defining the relationship between spend and profit return

  • Scatter graphs allow us to see relationships in data
  • In this example chart, used for illustration, we can see the relationship between media spend and PROI, looking at print newsbrands
  • Percentage of total comms spend and the PROI
  • Each dot on the graph represents an econometric model case in the results vault
  • Here the data suggests that as the % of print newsbrands in the mix increases, so does effectiveness


Creating tertile groups of cases shows the profit return for low, medium and high spend levels

Profit return on investment

Profit return on investment (PROI) is the revenue generated by advertising campaigns divided by the profit margin for each client over the short to medium-term. It takes into account the media investment and the cost of goods or services, so provides a much clearer guide to advertising payback than simply looking at the revenue generated.

A key feature of this research lies in the concentration on total campaign PROI, as opposed to individual channel PROI. The most important thing is to prove the effectiveness of media on a total campaign level because this is what drives results and core business objectives.

It’s important to note that profit calculations have already accounted for all media and cost of goods, so any PROI figure of over 1.00 is paying back on top of the initial investment in the short term.

In this report, we’re concentrating on short to medium- term profit generation. This is increasingly the way that advertising is measured so it’s important to be able to prove the profitability of media channels in the short-term. This in turn will mean considerably higher long-term profit: Benchmarketing’s estimate of the long-term effect is twice the short to medium-term PROI.


Budget optimisation

The data from the meta-analysis allows us to build response curves for each media channel. This works by analysing ROIs across data points in each category to generate average response curves. Curves that “go flat” suggest high diminishing returns and no benefits to additional investment. We can take an annual budget and optimise the overall ROI for the spend, by changing the mix. It’s a simple hill-climbing optimisation that picks the highest and the slopiest points by medium. From the curves we can calculate the optimum media split for any given budget.


Creating tertile groups of cases shows the profit return for low, medium and high spend levels

Glossary of terms

Adstock (advertising carry-over) – advertising carry-over rates measure the time period over which the media will drive a sales response. 50% carry-over rate a week means that if there were 100 impacts in the week of the advert, then there would be an effect of 50 in the second week and 25 in the third. Carry-over is identified by best fit and statistical confidence within the modelling process. It greatly influences the total return of a campaign

Digital display – this refers to advertising online, in all of its formats (excluding search)

Established media – established media refers to media channels that existed prior to the relatively recent rise of digital media, such a print newsbrands or TV. It’s important to note that established media forms have adapted to the digital landscape to become multi-platform

Meta-analysis – a meta-analysis is a method for systematically combining data from several studies to develop ‘metadata’ and come to overall conclusions with greater statistical power than the sum of their parts (the individual econometric models that they’re made from). It’s common in clinical drugs trials in the pharmaceuticals industry. One trial isn’t enough, you need hundreds so as to be sure of your results. If all the trials come up with the same answer, that’s a very strong result. If the trial results are different, then being able to explain robustly why they are different – different dosage, different demographic sample – is again a result and new learning

Nielsen – Nielsen is an information and measurement company providing market research, insights and data about what people watch, listen to and buy. In this project, the data has been used to report offline media spend figures

PAMCo – Audience Measurement for Publishers is the new JIC (Joint Industry Currency) for published media, using approved, world-leading methodology. It produces de-duplicated brand reach, allowing users to carry out reach and frequency planning to better understand audiences across all platforms

PROI – ‘Profit return on investment’ – the revenue generated by advertising campaigns divided by the profit margin for each client over the short to medium- term. It takes into account the media investment and the cost of goods or services, so provides a much clearer guide to advertising payback than simply looking at the revenue generated

RROI – ‘Revenue return on investment’ – the amount of gross income versus the costs of an ad campaign. This is not overall profit, it’s sales revenue

Sales response curves – sales response curves take a dynamic look at the changes in response to advertising according to different combinations of channels at different budget levels

Scaleable – the ability to be resized to different proportions. In this project ‘scaleability’ refers to whether or not a media channel can be scaled up to take a higher proportion of the media budget and still deliver strong profi ts

SMI (Standard Media Index) – SMI provides global adspend data straight from booking systems. In this project, it’s been used to calculate the proportion of total adspend attributed to digital media channels

Tertile – a ‘tertile’ refers to one third of any given dataset. In this analysis, we talk about ‘low’, ‘middle’ and ‘upper’ tertiles

Traditional mass media – also referred to as ‘established media’, traditional mass media refers to large audience media channels such as print newsbrands or radio, which existed prior to the relatively recent rise of digital media. It’s important to note that ‘traditional’ have adapted to the digital landscape to become multi-platform


The battle for attention, Newsworks & PwC, 2016

Context matters: A brain science study revealing why ads in quality editorial environments are more effective, Newsworks, AOP & Neuro-Insight, 2017

How people buy, Newsworks, Flamingo and Tapestry, 2015

IPA Databank study 2017, Newsworks & Peter Field, 2017

Paying (for) attention, Lumen, 2017

Profit Ability: The business case for advertising, Thinkbox, Ebiquity & Gain Theory, 2017

Re-evaluating Media: What the evidence reveals about the true worth of media for brand advertisers, Ebiquity on behalf of Radiocentre, 2018

The ROI of digital newsbrands, Ben Dudley – former head of data modelling at Havas Media Group, 2017