A unified system fuses hindsight, insight and foresight to help manage short and long-term decision-making for an uncertain future

Planning for future uncertainty is a hot boardroom topic. It’s especially true now as we continue to deal with the fallouts from the COVID-19 pandemic: dramatic changes in customer behaviour, shifting media consumption, supply chain challenges and overall economic upheaval. 

History shows that, in times of disruption, organisational resilience depends on adaptability and decisiveness. Yet many organisations base decision making  on hindsight (understanding what happened) and insight (understanding why it happened).  



Living in a VUCA world

In a world now plagued with volatility, uncertainty, complexity, and ambiguity (aka a “VUCA” world) – hindsight and insight are no longer sufficient to accelerate sustainable growth and gain competitive advantage. 

To quote Professor Klaus Schwab, the founder and executive chairman of the World Economic Forum: “The pandemic represents a rare but narrow window of opportunity to reflect, reimagine, and reset our world.”

We now have an opportunity to reimagine how we manage uncertainty and navigate towards accelerated and sustainable growth. To do this, organisations need foresight. 

From uncertainty to manageable risk

Foresight takes uncertainty and turns it into manageable risk. It considers what is most and least likely to happen in the VUCA world and reveals the signposts and probabilities of them happening. 

Some fascinating examples of foresight already exist. Who would have foreseen, for example, that the Chinese e-commerce platform JD.com would outplay its competitor Alibaba by reliably delivering goods when lockdown hit (and increasing revenue by 21 per cent  in the first quarter of 2020) while Alibaba struggled to find couriers. Recruiting the right volume of couriers at the right time required foresight.

Whether it’s the shift to hybrid working, skyrocketing growth in e-commerce or chip shortages affecting the supply of new vehicles, VUCA events will continue to affect all organisations for the foreseeable future.

Scenario analysis by McKinsey shows that a single, prolonged supply-side shock would wipe out between 30 and 50 percent of one year’s earnings (EBITDA) for companies in most industries. The same study classified different types of shocks based on their impact, lead time, and frequency of occurrence, ranging from theft and common cyberattacks to pandemics and climatic events such as hurricanes. But knowing which possible events to focus on is not an easy task.  

The goal to accelerate digital transformation via online selling and marketing started in 2013 for L’Oréal. When the COVID-19 pandemic hit, the company was well positioned to shift ad spend online. In the first quarter to the end of March, ecommerce sales grew 53% in comparison to the previous year. L’Oréal had invested in this future lever of growth and it paid off handsomely at a time of unforeseen market upheaval. 

Diagnosis before cure

But how do you continue to make good decisions and successfully plan in a VUCA world? First, it’s important to understand what types of challenges your organisation is likely to face. Before you can cure, you must first diagnose. 

Are you facing volatility resulting from an unpredictable supply chain? Or uncertainty caused by new entrants competing with your products? Or complexity due to regulation changes? Or ambiguity raised by not knowing if the current vaccine will protect the population against new variants? Knowing the type of challenge, or combination of challenges, you face is an essential first step.

To make data-informed decisions that accelerate sustainable growth, organisations need faster, smarter, insights that are unified into a single version of the truth to understand what has happened, why it happened and what to do next.

Foresight is key to the unified version of the truth; it enables decision-makers to war-game and simulate; scenario plan and optimise; identify and track leading indicators and to understand the risk and impact of “wild card” events.

A single system for all-round future confidence

We have a unified decision-making system at Gain Theory – HiFusion – that fuses hindsight, insight, and foresight, across all sources and levers of growth, both known and unknown. It identifies long-term strategic opportunities and answers near-term tactical performance questions. 

In the HiFusion decision making system, there is a rich arsenal of foresight techniques to uncover future states of demand depending on the VUCA challenge faced: 

 Future Back Thinking: defining the desired future and then working backwards to identify the potential specific actions and signposts that connect the desired future to the present. For example, setting a target to be net zero carbon by 2030 might involve several potential actions such as planting more trees or swapping to solar power. However, the signposts, such as famine and food shortages, might indicate that planting trees is no longer an option and that we need to switch to solar power as land costs soar. 


• Delphi Method: developed by Project Rand in the 1950s, the method uses a group of experts who anonymously and repeatedly reply to questionnaires about the future, receiving feedback as a statistical representation of the group’s response. The aim is for the group response to converge after each iteration of the questionnaire, ideally resulting in consensus of expert opinion. While the overall accuracy is mixed, the method is used when looking at long-term trends in policy making and technology development.


• War Gaming Simulations: simulating different competitive settings and the impact on consumer demand. For example, the increase in demand for used vehicles during the chip shortage, depending on the duration of the shortage and the actions of competitors.

• Forecasting: projecting future events by taking signals from the past mixed with likely future states caused by internal and external factors and shocks, such as pandemics, international tension, climate change and competitor threats. For example, how will grocery evolve to meet the challenges of rising interest rates and potentially lower demand in 2022/23?


• Lead Indicators: measurable signals that provide an early warning system or prediction of what the situation could be in the future. For example, new car registrations used to be a reliable lead indicator of economic strength and consumer propensity to spend. But in the face of supply constraints, how reliable is this indicator today?


• Scenario Planning: making assumptions on what the future is likely to be and how your business performance might be affected, for the purpose of creating a more robust strategy. Often scenarios are run under “what if?” assumptions to work out the best possible path. For example, looking at the impact on both short and long-term sales and profit resulting from pulling all advertising in the final quarter of the year.

 Trend Analysis: collecting qualitative and quantitative information to spot patterns or new trends, and thus paint an indicative picture of what might happen. These trends can often be used later in scenarios. For example, Wunderman Thompson’s “The Future 100: 2022” which forecasts 100 trends to watch in the coming year or GroupM’s “This Year Next Year” forecast of ad spend, used to augment media response curves in future marketing campaigns.

By fusing hindsight, insight and foresight, HiFusion enables organisations to identify future sources of growth and give confidence to decision-making across all levers of growth. It enables organisations to invest in the right data sources, technology, and methods to confidently answer questions around: 

• the role of brand equity and customer experience in maintaining price resilience

• the short and long-term impact of investments

• drivers of customer choices and product trade-offs 

• identifying and tracking signals that provide an early warning system

• targeting new audiences based on their motivation

• acquiring new customers in a cookie-less world of walled gardens

• conducting complex multi-test-and-learn experiments at scale

• preventing customer churn

• growing spend from existing customers by making the right recommendations

• …and, ultimately, judging correctly what is likely to happen in the future.


HiFusion creates a holistic loop to support strategic decision-making by weaving foresight, insight and hindsight across time horizons and a range of stakeholders. It unifies tactical execution, plus annual and longer-term strategic planning into a single measurement system. 

In a VUCA world, navigating the range of future possibilities to accelerate sustainable growth requires an organisation to invest with confidence. Foresight gives us the ability to manage uncertainty and, ultimately, create and tap into future states of consumer demand. 

By knowing tomorrow, we can disrupt today. 

This article was originally published in Campaign – click here or download the PDF on this page.

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Summary: 

  • We live in an uncertain world, where accurately predicting the future is nigh-on impossible.  
  • Companies that want to accelerate growth will use data and analytics to look at a range of likely outcomes to make data-informed decisions on where to place bets.  
  • Gain Theory has helped ambitious brands understand the likelihood of a range of outcomes, leading to more confident bets.  

Navigating Probability in a Time of Flux  

Uncertainty rules the roost. Covid, the state of the economy, demographics, trading patterns, logistics are all in a state of flux. To say nothing of environmental challenges likely to arise through changing consumption habits and government regulation. The slowest rate of change was last year and so using foresight capabilities to steer decision making has never been more important. 

With so much change, brands need to plan for many different contingencies. And they need to recognise which signposts are the most important in signalling that one outcome has suddenly become more likely than others. By explicitly modelling the probability of different contingencies we can help translate this uncertainty into quantifiable risk. 

The Direct and Indirect Impact of States of Flux  

To focus on just one example, consider the economic situation. We know that the state of the economy has a fundamental impact on the ability of all companies to grow their business sustainably and profitably. The economy can have a direct impact, the less confident people are, the less money they have in their wallet, the more they’re likely to seek value, and vice versa. But the economic backdrop can also have an indirect effect, changing the impact that each marketing $ invested has as the economic situation changes. 

We know that this indirect impact can be dramatic. In a recent analytics project, we found that the average uplift on sales of all marketing levers was worsened by almost 30% as key economic variables moved against them.  

Using probability theory to determine potential outcomes and manage risk  

Now, what does this mean going forward? Well, it depends on our expectations of where the economy will be over the next 12 months. Will it improve or worsen? If it improves, will it be a little or a lot? And what do we mean by “a lot”? 

hindsight vs foresight

This is where foresight comes into its own. Using an approach grounded in probability theory we can determine how likely each potential outcome is. We’ve shown this for youth unemployment in the chart – we have a central projection (solid line) and a range of feasible outcomes either side of this. 

The further we get from the central projection, the less likely the outcome. For example, looking at worsening unemployment we can see that while it is possible to jump to a rate of 15% by Q4 2022 it is not very likely. In fact, there is just a 2% chance that the outcome will be as bad as that. So, we shouldn’t spend too much time scenario planning around this.  

But there are a lot of credible scenarios where youth unemployment could move by 1 or 2 points – from roughly 10% today to say 12% by mid 2022. There is a smaller chance that it will stay at current levels. What plans can we put in place now that means we’ll be ready for each eventuality. Business plans that have a ‘business as usual’ approach baked in will almost always lead to poor performance. Alternatively, plans that have uncertainty baked in will generally perform much better and the executives using these plans will have more control over their future. 

Using these and similar techniques, Gain Theory is helping brands to navigate the future, using foresight to translate an uncertain world into more manageable contingencies.  

Exec summary:

Privacy updates made by Google and Apple will have implications on how media is delivered, what information can be captured, and how media performance can be measured.  These actions won’t kill major sectors of digital media and media measurement, but they will create significant challenges.  New processes will need to be built to account for these privacy restrictions.  These new processes will likely favor larger media partners which will continue to fuel media consolidation.  We expect that these updates will drive adoption of more privacy-compliant Multi Touch Attribution alternatives such as Gain Theory’s Sensor.

Key implications:

  • How legislation (GDPR, CCPA) and business decisions by the major internet browsers (Safari, Firefox, Chrome) have limited data capture, media delivery, and measurement over the past few years
  • How Google’s decision to block third-party cookies/tags will impact Chrome
  • How Apple’s release of iOS14 will impact user opt-in requirements on apps
  • The difference between “first-party” tags and “third-party” tags and the implications on consumer data capture and media delivery standpoint
  • The implications of third-party tag and cross-app restrictions on AdTech, i.e. the challenges of server-to-server integrations to audience pool sizes, retargeting, and implementation bottlenecks
  • The impact on Multi-Touch Attribution and potential alternatives such as Gain Theory’s Sensor
  • Media consolidation and how it plays to advertiser’s ability to create contextual audience targeting

Legislation and business decisions have limited data capture, media delivery, and measurement

Over the past few years, a combination of legislation (GDPR, CCPA) and business decisions by the major internet browsers (Safari, Firefox, Chrome) have made data capture on the open internet and via Apps more restrictive.  Legislation broadened (or formalized) the definition of PII (Personally Identifiable Information) for the digital age.  This broadened definition created a potential liability issue for non-compliant business (e.g. everything needs an “opt-in” now).  At the same time, the browsers and web operating systems have begun rolling out privacy features for several reasons: to protect consumers, to comply with legislation, and to avoid liability.  Beyond the basic implication that these events limit data capture, they also by proxy impact how media is delivered and measured.

Where we are right now?

Two major events are unfolding currently:

1. Google will soon be blocking third-party cookies/tags “by default”, joining Safari and Firefox, who are already doing so. 

Chrome represents a clear majority of U.S. web browser installs.  When Google activates this change, the impact will be huge.  Between the three browsers, 90+% of browser-based internet activity will have third-party tags blocked by default.  For definition, “by default” means the user of the browser would proactively have to opt-in for third-party tracking…but why would anyone do that? Once Google releases the Chrome update, consumers will begin updating their software and buying new devices.  As consumers start doing this, the % of third-party tags blocked by default will grow until it’s virtually the full Chrome user base.

2. The release of iOS14 Apple will require users to opt-in for IDFA (The Identifier for Advertiser) cross-app tracking, on an app by app basis. 

IDFA is Apple’s “Identifier for Advertisers”.  This will limit an app’s ability to see a user go to another app on the same device.  Cross-app tracking is similar in nature to third-party tagging (as described below) but one could argue that it’s easier for an app to make the case for how cross-app tracking can be a benefit to the consumer.  For instance, American Express could argue that allowing their app to be able to talk to the apps of their business partners could be a benefit to their cardmembers.  Since this iOS opt-in is at the app level, the consumer will be able to choose if they want to allow American Express cross-app tracking. As iOS14 is released, consumers and app owners will begin to face this choice very quickly.  And as consumers update their iOS and buy new devices with it pre-installed, it will become standard across the iOS ecosystem.

Why are third-party tags and cross-app tracking important?

Firstly, let’s look at the difference between “first-party” tags and “third-party” tags:

  • First-party tags: When a consumer is on Amazon.com, Amazon can track that visitor via first-party tags.  “First-party” in essence means the company doing the tracking owns the website the consumer is on.  This is akin to a shopper being in your brick and mortar store; they’re on your property therefore you have the right to observe where they go. 
  • Third-party tags: this is when the company who owns the “tag” is not the owner of the website the “tag” is placed on.  This allows the third-party to track consumers on sites they don’t own.  In the real world, this is akin to companies following people around all day and logging everywhere the people go and when.  This would obviously be a breach of privacy.  But on the internet, this is exactly what third-party tags had enabled companies to do unrestricted up until now. 

So, what were the implications? 

AdTech was basically built around third-party data capture.  Picture this: if a company places third-party tags across several hundred websites and paid media ads, capturing all the data of consumers hitting those media properties, that company could create a fairly accurate representation of internet behavior.  They could then mine their repository of cookies, all their associated behaviors, and leverage the data to deliver targeted media to their pool of cookies. 

Companies have been doing this for well over a decade.  And while cross-app tracking isn’t exactly the same as third-party tags it enables many of the same things: broad data capture, retargeting, audience/creative optimization, etc. 

If companies can’t use third-party tags and cross-app tracking, is AdTech dead?

No, AdTech isn’t dead. But it has to change.  There is a new approach to data capture that has come along to replace third-party tags and cross-app tracking: server-to-server integrations (S2S).  A server-to-server integration is when ABC.com matches its users to XYZ.com’s users so they can see the overlap in users on their sites.  Doing this is a bit more restrictive than what’s possible with third-party tags; ABC and XYZ need to have shared data elements they can match on.  They would typically match on an encrypted email address.  Net/net, they can only match consumers that have registered on their sites; they can’t match general visitors.  As a result:

  • Shareable audience pool size shrinks
  • Major implications on retargeting and, more generally, at any time digital audiences are created
  • Implementation bottleneck: for instance, Facebook can’t just do a server-to-server integration with every major media property and/or client overnight.  Right now, they have a waitlist that could be upwards of a year

Measurement implications: Is Multi-Touch Attribution dead?

No. However, everything above implies severe limitations as these changes take effect.  The challenge is that it will become increasingly difficult to create a “complete” user path of media touchpoints that led to a conversion.  There were always challenges at play, but they will only become worse.  Server-to-server integrations will become the major way raw media data gets stitched together across platforms by players such as LiveRamp, but they, too, face challenges due to the blocking of third-party tags (which LiveRamp uses heavily). Since server-to-server integrations only work for registered site visitors, not general visitors, the audience scale and matching accuracy of partners such as LiveRamp will suffer. However, with data integrators such as LiveRamp it is nearly impossible to actually QC their work; it’s all anonymized.  As a result, the true gaps created by the loss of third-party tagging and the switch to server-to-server integrations may never be known; this could sew distrust within the Multi-Touch Attribution (MTA) ecosystem, for example, raising questions like, “how accurate is this?”  Measurement partners will still deliver MTA solutions to clients but will the accuracy decline?  The marketplace doesn’t quite know yet.  If it does suffer, we can expect to see clients begin to reevaluate their measurement needs and become open to other near-term measurement solutions like Gain Theory’s Sensor

Media consolidation is at play as well

While this privacy battle has unfolded there has been significant consolidation in media.  We’ve seen the rise of major video platforms like Hulu, YouTube, etc.  These platforms have an endless supply of video content and consumers are typically logged in when they use them.  These two factors enable a massive amount of contextual understanding of the consumer. Given the scale of these platforms, and their ability to target, we’re seeing a massive shift towards contextually targeted media.  These platforms simply know so much about their massive audiences that they don’t need digital behavior data from outside their ecosystems to optimize media delivery effectively. 

Long story short, the large streaming video partners aren’t being hamstrung very much by the blocking of third-party tags and cross-app tracking.  And consumers’ attention and media consumption will continue to centralize around these platforms.  This means that with a handful of large-scale server-to-server integrations across these platforms, plus Google, Facebook, etc, we will be able to see a very comprehensive view of users’ digital media consumption. In the future, there will simply be fewer “critical” media partners, and all of them equipped with logged-in users.  This will make it easier to integrate a handful of major players than it was to track hundreds of third-party tags on mid-tier media partners.  Eventually, new measurement solutions or measurement workspaces like “white rooms” could become much more prevalent and holistic.

As originally published in The Drum, 13th May 2020

Although it’s a precarious time to make sweeping business changes, Gain Theory’s Russell Nuzzo makes the case for Near-Term Measurement in lieu of marketers’ favourite – Multi-Touch Attribution. 

Every organization is asking the same question: if the world economy is frozen, what can I cut that will still allow me to come out of the running blocks fast? Unfortunately for many marketers, the decisions around investment cuts are being made by finance, with only the savviest of chief marketing officers having a say. 

Right now, marketers need to justify every dollar by using the most accurate and relevant data possible to make fast decisions that will have a positive impact. In this climate, businesses that can, need to generate revenue now. 

If return on investment was important for advertisers before the Covid-19 outbreak, it’s absolutely mission-critical now. And for marketing measurement, if anything good can come of the current crisis, it’s that brands begin a renewed focus on mastering what we call ‘near-term performance measurement.’ This approach focuses on using immediate and precise data signals to make advertising decisions. 

Simply put – this crisis requires a strong, data-oriented approach for how we gauge the effectiveness of advertising. It’s time to zero-in on the data that is actually going to help you impact and protect your business immediately, rather than seek solutions through overly complex approaches with highly imperfect data. 

Understandably, the temptation will be to plug the near-term ‘water leak’ by using the multi-touch attribution (MTA) ‘hammer’ that sits in the marketing measurement toolbox. But the ‘hammer’ is not the only tool you could use. 

Historically, brands have tried to be as strategic as possible with their marketing spending using established approaches such as marketing mix modeling (MMM). These models help big brands figure out how best to allocate their budgets to maximize key measures such as reach and sales and evaluate tradeoffs. 

However, if we recognize that the next six-12 months will look nothing like the past two to three years, the old models may no longer apply. MMM should not be thrown out; it can provide a great framing exercise. But it needs to be coupled with a strong, near-term measurement solution that can read and react based on what’s happening right now. 

And if brands don’t get ‘right now’ right – their future isn’t necessarily guaranteed. 

MTA is not the Swiss army knife that marketers need 

Not long ago, MTA was once the darling of the marketing industry. Conceptually, it’s understandable. Who wouldn’t want to figure out exactly which ads drove which action? Even better, it promised marketers the ability to discern how different ad units across multiple media channels worked together to influence consumers and drive action. That’s essentially marketing’s holy grail: reach exactly who you want and don’t waste any money. 

On paper, this is exactly the kind of tool that would be valuable right now, as chief marketing officers grapple with maddening business questions. But MTA has consistently overpromised and underdelivered. 

A slew of less than satisfied customers can attest to this. I have heard of projects that take more than a year to get off the ground, significant data gaps and difficulties distilling tangible insights, not to mention the challenges of integrating MTA outputs back into clients’ adtech stacks. The continued deterioration of third-party cookies and IDs – the linchpin of MTA – will culminate in 2022 when Google, having followed Safari and Firefox, will begin blocking third-party cookies in Chrome. 

Now is the perfect time to re-evaluate the right tools for near-term measurement. 

The right tool for the right job 

While the climate will be challenging for the foreseeable future, creating a unified, near-term measurement solution coupled with robust scenario planning, fueled by the latest available data will be essential. 

There can be no garbage in and no garbage out. Not now. 

To fuel near-term measurement, a tried and tested data-led alternative is to lean into what we call ‘micro-geographies’ for targeting as opposed to cookies. It is much easier to determine where an ad impression was served than who it was served to. Plus, micro-geographies are far more stable from data validation and privacy standpoints. 

Additionally, most external impacts to consumer buying decisions happen geographically; local pricing, local distribution, local weather, local competition – even local Covid-19 infection patterns can affect the decision to purchase something. 

We have been able to build these local features into our near-term measurement solution sensor; a micro-geography-based alternative to MTA. 

For Covid-19 specifically, we’ve been able to build a set of indicators to quantify how the outbreak is positively and negatively impacting brand sales. Some of those trends are short term but others may have longer-term impacts on brand preferences and consumer habits. Some of the impacts will fundamentally change business models permanently. 

Pivot to near-term measurement 

Organizations need an understanding of short-, medium- and longer-term impacts of all their current investment decisions, not just marketing. Alongside longer-term scenario planning using simulation techniques such as agent-based modelling as well as established techniques such as MMM, marketers also need an immediate view on the here and now. 

We think near-term measurement is the ultimate replacement for user-level MTA, and the perfect tool in the box for marketers in the Covid-19 ‘new normal’ landscape. Using near-term data can also predict consumer patterns before they happen. 

Now more than ever, marketers need to make data-informed confident decisions at speed. 

Using the right tools for the job, rather than reaching for a hammer, will help articulate the impact of investments ensuring brands remain relevant and robust through turbulent times, and that much better situated to lead when things get back ‘normal.’ 

Right now, marketers are beset by reduced budgets, lack of actionable data about customers, and rapid demand & media habit changes. Data, assumptions, models, and plans older than 45 days are redundant. Now is the time to prepare for the ‘known unknowns’ and pivot rapidly.

We are living through a generational spike in uncertainty, volatility and complexity.  No one knows the full human toll and economic costs of SARS-CoV-2 and the disease it causes, COVID-19.  This demand collapse is deep, sudden, and touches so many industries a global recession seems inevitable.  Consumers are using products and services they haven’t previously, and necessity is driving them to new paths to purchase.  According to the science of pandemics applied to current data, infection rates will keep going up so assume significant impacts on the concerns, moods, and the economics of your customer base.  They will engage your brand differently, if at all. The ‘old’ norms around brand preferences need stats and price sensitivity requires a new lens.

We recommend you transition rapidly and thoughtfully into the ‘new normal’ using early data and existing insights.  Here’s how.

Assess your situation, rapidly and accurately

At the risk of being dramatic, this is a survival situation for many businesses. One of the first things to do in a survival challenge and preparing for the ‘known unknowns’ is to deepen your situational awareness.

  • Look for analogous situations that inspire your response options. For example, case studies from brand behaviors in the last recession or in the aftermath of 9/11.  An article in Harvard Business Review from 2008 argues for spending in recessions: “It is well documented that brands that increase advertising during a recession, when competitors are cutting back, can improve market share and return on investment at a lower cost than during good economic times’. Also, consider cases of ‘forced trials’ i.e. customers trying competitor brands out of need: will they bounce back to you if they have a positive brand experience elsewhere?

  • Consider digital business model acceleration, product, partnerships and distribution options: Go beyond communications and start asking yourself: how fast can you ramp up your e-commerce capabilities? What product/service modifications can you pivot to? Can you partner with ‘complimentary’ brands to literally deliver your value proposition differently and address current customer needs?

  • Revisit the basic heuristics of price sensitivity and segmentation.  Heighten your sensitivity to both. How much of your business was driven by consumers/segments that are quite suddenly trapped at home?  Unemployed?  How intense was price/value competition prior to the pandemic?  Does your current marketing spend keep you appropriately messaged and top of mind to prevent leakage to competitors for key consumers?  Broadly, maintaining investment in brand to support the value proposition can mitigate price sensitivity.

  • Assess whether you are using the right marketing channels to communicate.  Current media data is clear on short-term consumption shifts, your channel mix also needs to shift.  Millions of your customers are at home driving the 30%+ spike in television viewing globally.  Viewing has shifted to general entertainment, given the lack of sports programming.  Consumers are reporting much more streaming since the outbreak, films and TV shows are up 60%+.  

Act now, triangulating with your best judgement

Most businesses are acutely focused on cash flow.  Demand plummeted faster than many cost structures could withstand.  In this harsh new reality, how much of your marketing and media investments are being eyed by your CFO?    

If you can maintain marketing investment  we recommend:   

  • Ensuring that your in-flight messaging is appropriate.  Dig deep into every crevice of your messaging and review, review, review.  Is your ‘old’ message appropriate now? What should we be communicating? What impact will your messaging have on brand perception?

  • Optimizing the channels you use.  Not all marketing spend can pivot on a dime, but media consumption habits have been forced to shift.  For example, while TV dollars are likely pre-committed, Digital, Paid Social, Paid Search can be adjusted quickly.  This logic needs to be applied to your entire mix.  Before you shift or reduce however, you must consider if you can serve short-term demand spikes, like in-home delivery, or if you are effectively at a stand-still, example you are an airline.

  • Using the channels with demonstrated prior strength until the fog lifts.  Perfect is not the key objective right now, presence is.  Monitor closely any potential drops in CPM across your marketing mix because some of your competitors might be forced to pull back.  Marketers willing to spend more with their partners are likely to benefit relative to those who cut, just as they always are.  Although it seems a long way off, H2 spending also needs to be a consideration in your revised plans.  

Look forward to re-igniting demand.

 “This too shall pass.”  said Abraham Lincoln.

COVID-19 has disrupted demand as we knew it and will re-write business models.  It may change forever how we market to, engage with and deliver our value proposition to the customers we have and the customers we want.  Events like these have real impacts on consumer confidence and therefore, habits. To get ready for the coming new normal, you must immediately think about the long-term effects of your actions today on the brand. In fact, 93% of consumers believe that brands should “stand up and help.” If your firm can do something to help the current crisis like donations, make those socially important actions and values part of your narrative.  Consumers have a long memory of these things and almost all of them have more time on their hands to watch what you are doing. 

By adjusting and adapting now, you will be ready to capture demand when it comes back. Let’s hope it comes roaring back soon.

Dear Marketers

We are in an unprecedented time of change and now more than ever need to work collaboratively to create solutions that help sustain business and the economy. As we progress through the next few months, bracing a new normal will become our new normal.

As marketers, you will have questions such as ‘will my brand survive?’  and ‘what can I do in the short term to protect my brand and then help it recover in the longer term’.

At Gain Theory, we are accustomed to using data to model uncertain scenarios, both in the long and short term. Many of the techniques used to forecast future impacts of marketing and media do not necessarily apply in this uncertain world. Whereas techniques such as Agent Based Modelling, currently used by governments to understand the impact of Covid-19, can also be used to help brands such as yours.

There are many ways in which to support decision making using data in an uncertain world.

To help guide you through this challenging time we are opening a brand-side marketer’s ‘helpline’ offering complimentary 30-minute Q&A sessions with our experts who will answer any questions you may have.

To join the sessions please email claudia.sestini@gaintheory.com.

In the meantime, if you’re just looking for decision making inspiration during these uncertain times, we’ve curated some quick reads below from our Marketing Measurement and Optimization experts to help stimulate your thinking and get you on your feet.

We will be publishing more articles to support you in making the right decisions over the coming months as the global situation develops.

Simulating Consumer ‘New Normal’ Behaviour to Answer ‘What if..?’

Classical economic theory assumes that individuals are rational. However, in the real world, we often see irrational behavior. In times of crisis even more so. Simulating potential consumer behaviours in the face of change can help brands with strategic planning and war gaming in the face of:

  • Demographic changes e.g. the implications of a younger or ageing population
  • Cultural changes e.g. recreational shifts from one activity to another
  • Competitive changes e.g. the emergence of new or alternative brands

One leading global brand approached Gain theory with a burning question:

What are the conditions that lead to seismic shifts in our market in which one category starts to grow and take share from others? Also, how can these shifts be anticipated in the future to give us a competitive advantage?

Our experts applied Agent Based Modelling, a simulation that reflects the real-world behaviour of a population. Their findings helped this brand forecast and plan for future market behaviour via:

  • Simulation of different trends and quantification of their potential impact on future sales within the market. 
  • Enhanced understanding of trend drivers and controllable factors. 
  • Testing of various scenarios and impact of doing nothing, launching a new product development, increasing media spend, or what might happen if the competitor does instead. 
  • Clear view on the impact of environmental changes such as working patterns shifting.

Brand vs Performance: Where should the Pendulum Swing?

Our experts give a point of view on what proportion of marketing budget should be spent on brand advertising and performance advertising. They examined 3 scenarios:

  1. Taking a brand off air
  2. Spending heavily on brand
  3. Spending heavily on performance

Three scenarios are below or you can read the full article here:

1. Taking a brand off air

If brand spend is cut, there can be a short-term improvement on profitability.  However, in the longer term we’ve seen profitability go negative, due to the lost sales outweighing the cut in costs.  One client of Gain Theory, a short term $0.4m gain turned into a $1.1m loss. Erosion of brand metrics follows: we’ve seen clients where brand metrics have declined for at least 3 years following a cut of brand advertising.  It is then harder and takes longer to recover from this and in that client, we subsequently quantified a negative effect on sales of 20%. So, while this approach can be appealing to hit short term targets, it can be hugely damaging in the long run.  This leaves one asking: is it worth it?

2. Spending heavily on brand

Some businesses will invest significantly in brand for a specific purpose, for example to build awareness or tell stories to keep the brand feeling relevant and alive for customers.  This type of investment can be a brave decision for marketers without appropriate measurement, as there is unlikely to be an immediate sales result.

One of our clients invests significantly in their brand advertising throughout the year.  They view this as crucial to maintaining their strong brand position in the market and place importance on tracking brand metrics to measure its impact.   They also see this spend build sales in the long term.  To balance out this heavy brand advertising, this client will also pulse with performance campaigns to ensure they are also meeting sales expectations in the short term.

3. Spend heavily on performance

In some clients, we’ve seen a move towards heavily investing in promotions.  Unsurprisingly, this shows immediate uplifts in sales and profit.  As well as producing seductive metrics, it can also be very attractive from an investment POV.  And there’s nothing inherently wrong with that – everyone needs to drive sales.  However, taking a longer view, we’ve seen clients where significant spending on price and promotions brought a negative impact on the brand and value for money metrics.

Demand Generation: 9 Golden Rules

Senior Partner, Matthew Chappell gives us a practical best practice campaign measurement guide that will enable businesses to effectively evaluate, learn and grow their media returns. 

For the downloadable version click here.

For the video presentation ‘Demand Generation’ click here which covers (a) How to balance trade off decisions (b) 9 golden rules of measurement (c) How Kellogg’s are accelerating analysis.

The 9 Golden Rules:

  1. Define success. Avoid the Texas sharpshooter fallacy: Painting the target once the shots have been fired.
  2. Use a level playing field. Treat every channel alike. Think about the metrics used for (a) inputs (b) outputs and (c) outcomes.
  3. Know your fundamentals across all media channels. Cost per thousand impressions, cost per TVR, viewability, advertising context etc.
  4. Right methodology, right job. Don’t use partial advanced analytics methods, like digital attribution, for holistic challenges.
  5. Triangulate. Seek consensus from multiple sources.
  6. Timely results. Be honest and realistic about what can be delivered.
  7. Be choosey about metrics. Don’t succumb to death by data.
  8. Allocate budget towards testing. Don’t optimize into a corner Be prepared to fail and learn.
  9. Context is important. Context changes so what worked in the past, might not work today. Apply human judgment to assess when this is true… and what to do next.

Avoid Analysis Paralysis

Lindsay Egan, Partner lends her counsel on how to make best use of insights and not fall into analysis paralysis.

Full length article found here.

Key takeaways:

  1. Align on ROMI: We often hear that different pockets of the organization have very different definitions of ROMI (Return on Marketing Investment). No one wants 5 different yard sticks to measure success by. Have an open and honest conversation about what the drivers of your business are.
  2. Hold your team accountable: this involves: clear expectations; clear capability; clear measurement; clear feedback and clear consequences.
  3. Triangulate Decision-Making: in light of the current climate it is particularly important to look beyond analytics models to understand marketing performance optimization opportunities. Who is the target audience? Is there an opportunity to invest more into specific marketing channels? What additional media is in the market? What will the next 2,4 and 6 weeks look like?
  4. Partner closely with your analytics teams:  give crystal clear direction on what the types of marketing decisions you need to make, when you need to make them and the format you need them in. This will guide your analytics teams on the insights they need to generate and help them figure out the best marketing analytics solutions to deliver.
  5. Involve your media agency and activation partners early: this will ensure everyone is aligned with coming up with the best solution.

Amongst the corridors of marketing, one of the long-standing debates is what proportion of marketing budget should be spent on brand advertising and performance advertising.

The issue can be viewed as a pendulum, which swings between the two extremes of pure brand or performance marketing spend or is more often stuck at a point in between. In our experience, there are three reasons behind the pendulum’s resting position:

  1. Many structural factors will come into play e.g. a brand’s sector, cycle, business model or strategy will all feed in to where the pendulum currently lies.
  2. The impact of performance marketing spend is often quick and easy to measure, whereas the impact of brand spend can be more challenging to determine. This often tips the balance in favour of performance, where instant results can be easily produced.
  3. In many organizations there is a prevailing short-term mindset, which brings a focus on short term results. This again means a swing towards performance, as any brand impacts will likely only appear over the longer term.

We’ve worked with brands at various positions on this pendulum, and the results we’ve seen are really interesting…

  1. What happens when you take brand off air?

If brand spend is cut, there can be a short-term improvement on profitability.  However, in the longer term we’ve seen profitability go negative, due to the lost sales outweighing the cut in costs.  In one client of Gain Theory, a short term $0.4m gain turned into a $1.1m loss.

Erosion of brand metrics follows: we’ve seen clients where brand metrics have declined for at least 3 years following a cut of brand advertising.  It is then harder and takes longer to recover from this and in that client, we subsequently quantified a negative effect on sales of 20%.   So, while this approach can be appealing to hit short term targets, it can be hugely damaging in the long run.  This leaves one asking: is it worth it?

  1. What happens when you spend heavily on brand?

Some businesses will invest significantly in brand for a specific purpose, for example to build awareness or tell stories to keep the brand feeling relevant and alive for customers.  This type of investment can be a brave decision for marketers without appropriate measurement, as there is unlikely to be an immediate sales result.

One of our clients invests significantly in their brand advertising throughout the year.  They view this as crucial to maintaining their strong brand position in the market and place importance on tracking brand metrics to measure its impact.   They also see this spend build sales in the long term.  To balance out this heavy brand advertising, this client will also pulse with performance campaigns to ensure they are also meeting sales expectations in the short term.

  1. What happens when you spend heavily on performance?

In some clients, we’ve seen a move towards heavily investing in promotions.  Unsurprisingly, this shows immediate uplifts in sales and profit.  As well as producing seductive metrics, it can also be very attractive from an investment POV.  And there’s nothing inherently wrong with that – everyone needs to drive sales.  However, taking a longer view, we’ve seen clients where significant spending on price and promotions brought a negative impact on the brand and value for money metrics.

What’s the solution?

Ultimately, there is no silver bullet to determine where you should be on the pendulum swing, and marketers will need to flex according to their business strategy.

But marketers need to remember that accountability is key: finding the right way to measure brand spend in a fair comparison with performance spend will help to conduct this debate objectively.

Our recommendation is to define a holistic measurement strategy as a first step.  This allows brands to quantify the impact from all their marketing, providing a view of real financial results.  Once this measurement is in place, the best decisions can then be taken to meet total company targets and find the optimal place on the pendulum swing.

Further resources:

Long-Term effects of Advertising: Gain Theory’s research for the ProfitAbility report click here

Marketing Effectiveness Strategy: commissioned by EffWorks in conjunction with brands representing £7bn in ad spend click here

It’s a long journey from the classroom to the C suite, and managing a global organization isn’t a job many people can relate to. So, what is that journey like? What are the lessons learned? What are the leaders really like behind closed doors?

In this exclusive and candid WPP Stella podcast we hear from Manjiry Tamhane, Global CEO at Gain Theory in conversation with Jay Kandola, Commercial Director at Mediacom talk about her journey to the C suite, perspective on life and leadership.

Highlights include:

  • Manjiry’s journey from university graduate to Gain Theory CEO
  • Why being brave is vital to success
  • What makes Gain Theory special
  • The book that had the biggest impact on her
  • On building data informed cultures
  • How to deliver marketing excellence
  • …and why shy bears get no honey!

Listen to the episode below, if you enjoy it, share it!

Stella Conversations is a series of informative and inspiring conversations between members of the WPP Stella women’s leadership group and a cohort of future leaders.


In June during the Cannes Lions Festival of Creativity, Gain Theory Global CEO, Manjiry Tamhane, and Howard Grosfield EVP & GM US Consumer Marketing at American Express took to the stage to talk brand purpose and Marketing Excellence at the CMO Club House.

Below are the key takeouts, originally published on the CMO Club website.

To join this innovative and engaged community of CMOs, committed to helping each other solve their biggest challenges in a behind closed doors, candid, and trust-worthy environment click here.

Key Takeaways

  • Marketing is the engine of business growth.
  • We find a lot of conversations are about being data-driven, but it should really be about how data is used to inform the decisions within an organization.
  • Organizations that ground their decisions in data outperform on revenue by 85% against their peers.
  • You need to have a deep understanding of the purpose of your brand and then permeate that meaning to the front lines of your organization. If you do both of these things together, that’s excellent marketing.
  • When marketers excel at what they’re doing, you get sustainable business growth.
  • We aren’t trying to be the largest Bank or credit card company. We wake up wanting to deliver the world’s best customer service every single day, even if that involves us moving into new markets or engaging with our customers in new ways.
  • We’re a data-rich company. Our problem is not getting data. We have 120 million cards used around the world, but we need to be surgically precise on how we use this data to drive engagement. When customers tell us what they need, we pivot.
  • There’s a divide between those who think it’s about creative and those who think it’s about data.
  • For those of us in heavily regulated industries where every marketing message needs to be approved, the gift of agile is being able to seat the copy person, the creative person and the compliance person round one table, and do what the customer wants us to do.
  • Questions marketers are asking, “How do I educate and upskill my people,” and “How do I change the process?”
  • The marketer’s challenge a few years ago was getting their hands on data, removing jargon from the industry and asking a simple question without getting different answers. Now marketers have the data, know the jargon, and have the answers. The challenge is how to make decisions quickly, and how to become data rich but not insights poor.
  • Manjiry Tamhane says; “My Mum gave me determination. She’s as stubborn as anyone you’ll ever meet. My Dad was an architect so from a creative industry, and it created a beautiful blend of my mom’s data brain combined with his creativity.”
  • Howard Grosfield says; “My parents were tremendous role models. They taught me that people rarely remember what you say, but they always remember how it made them feel. We’re now in the feelings business, that advice has translated well into my career.”

Karen Kaufman, Global Chief Strategy Officer at Gain Theory speaks to AdAge in an article about the barriers keeping marketers and organizations from leveraging their data to inform decisions.

Closing the gap between marketing analytics and performance

Many marketers today have measurement systems in place to gauge the impact of their marketing campaigns. When ROI estimates reveal that a campaign is falling short of expectations, a decisive and well-informed marketer will reshuffle the media mix, change up the creative or take some other corrective action.

Unfortunately, this level of rigor is not being applied consistently to marketing investment decisions. Data and analytics are a gold mine, but marketers are not fully incorporating this intelligence into their decision-making process.

The fact is data and insights often languish inside the organization, resulting in organizations that fail to achieve the full potential of their marketing investment.

Research confirms a disparity between spending on data and analytics and a marketer’s willingness or ability to make decisions on the basis of its conclusions.

Currently, marketers spend 5 to 7% of their overall budgets on data analytics. According to the CMO Survey, that number is expected to jump to 11.3% in the next three years. And yet, in 2019, fewer than half (43.5%) of all business decisions are being made on the basis of marketing analytics—the highest level in the last six years. Moreover, when respondents were asked “To what degree does the use of marketing analytics contribute to your company’s performance?” they gave an average rating of just 4.1 on a scale from 1 (“none at all”) to 7 (“highly”).

The numbers seem remarkably low, especially considering the high levels of investment. To the casual observer, they raise the question: Why would a company commit resources to marketing analytics—or any data asset—without an obvious benefit to the business?

For starters, many marketers approach the need for data analytics as simply “checking a box”—in other words, for its own sake rather than with a clear understanding of the business question the marketer is trying to answer. There is an urgent sense of “I’ve got to do [fill in the blank] because everyone’s doing it.” That’s one sure way to get stuck in the weeds and by no means a path to marketing success.

Turn actionable insights into action

By now, it is widely accepted that one of the main goals of analytics is to produce “actionable insights.” Many successful marketers already possess the necessary insights to better engage with consumers. The issue is not so much the insights per se, but rather it is the ability to implement those insights by key decision makers across the organization that usually represents the biggest hurdles for marketers.

At Gain Theory we know this to be true from our own research findings. In one industry study, we asked marketers, “Is your company able to act on insights?” The answers we got back were mixed. Some marketers were unable to take action on key insights because they lacked a mandate from senior management while others got bogged down in a process of testing the efficacy of the findings before widely implementing the lessons to other departments. One respondent summed up, candidly, “We sometimes apply data without logic or experience.”

Design solutions for the end user

Today’s marketing technology space includes an abundance of tools powered by precise statistical models. Yet most of these tools were not designed with the marketer in mind. They can be overly technical and cumbersome to use.

We set out to correct this problem when developing our new marketing decisioning platform, Gain Theory Interactive. We conducted interviews with marketers and brand teams to fully understand how decisions are made. We learned that marketers need to be able to make critical decisions—often on the fly—and they need tools that empower them to make those decisions without requiring expertise in things like regression models.

Our main goal was to build a platform for marketers that simplifies the user experience and makes the output clear and easy to understand. The platform’s landing page, for example, immediately gets to the crux of the business question, whether it’s determining the budget required to achieve a sales target or informing the right marketing mix for a planned spend. As users go deeper into the platform, the steps and required inputs are designed to reflect how marketers tackle real-world problems.

Consider how the iPhone has revolutionized not just how we work but how we handle practically all aspects of our daily lives. Yet few if any of us ever think about the nitty-gritty details of the technology that makes our gadgets work right out of the box. With a platform that enables marketers to make informed business decisions without having to be experts in analytics—or taking the time to consult with a team of data scientists—marketing can achieve its fullest potential.

Article originally published on Adage click here.

Find out more about Gain Theory Interactive by visiting the site here 

 

 

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