Gain Theory, a global marketing effectiveness consultancy, is included in Forrester’s report “Three Requirements Every CPG Marketer Needs to Select a Marketing Measurement Vendorreleased May 6, 2020.

Forrester’s report details how CPG marketer’s measurement needs differ from those of marketers in industries with greater access to consumer data and outlines the CPG-specific capabilities needed from partners to optimize marketing budgets.

Gain Theory’s consulting-first approach provides its clients with marketing analytics, training, data strategies, and help building marketing strategy recommendations.”

The Forrester report states that B2C marketers in the CPG industry have minimal access to customer-level data. Due to using third-party distributors, like grocers, and indirect relationships with customers the availability of customer-level purchase data is severely limited.

Therefore, CPG marketers require unique marketing measurement approaches and rely upon robust assistance with data and analytics to understand the impact and results of their marketing campaigns.

Gain Theory is cited as a vendor that has the specialized capabilities and experience that CPG marketers need. Specifically, the report notes:

  • Gain Theory’s cloud-based decision-making platform Gain Theory Interactive “collates vast amounts of performance data across brands and geographies, enabling fast marketing optimizations”.
  • Various data assets Gain Theory can access, including, its own proprietary US tracker. “These data assets have information including but not limited to customer behavior, brand insights, and marketing investment data, which can be analyzed together to better understand marketing efficacy.”

Gain Theory has also been named a Strong Performer in The Forrester Wave™: Marketing Measurement and Optimization Solutions, Q1 2020 and is proud to be on Forrester’s shortlist for CPG marketers in this 2020 report.

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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.’ 

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

The analytics era seems to finally have arrived in marketing. 

The question is, “Are marketers actually ready?”

For example, three-quarters of brands say they are spending more on marketing technology this year, with 24% claiming to be spending significantly more, according to a recent Forrester report.

It looks like marketers are finally taking this seriously.

At the same time, just 10% of brands in that report say they have a clear picture of who their customers actually are. Not just the data, but who they are as people, and how that affects their consumption habits.

Something’s not right here. I suspect we know why.

We’ve heard more than a few stories like this. A major marketer is fixated on using advertising to drive acquisitions and wants to better manage its return on investment. So, it turns to one of the many technology partners in the market for help in building a multi-touch attribution (MTA) models.

The marketer is excited about the promise of better analytics, so they invest a significant amount of time and money along the way. Then they start getting insights back, and realize they have loads of questions they can’t answer, such as:

“Are these numbers good or bad?” 

“What is success?” 

“What should we do with this information?”

“How do we take this insights and move our budget to places that will drive more acquisitions?” 

Faced with all these fundamental questions, instead of taking the bold action they dreamed about, the marketer freezes. Eventually the company abandons the MTA tool with little to show for their investment.

Like I said, we’ve seen and heard lots of stories like this. We can help make sure this doesn’t happen to you.

Making effective marketing decisions is complicated. 

There are many considerations to determine which strategies are working and which ones aren’t, but that’s only the first piece of the puzzle. Once you figure this out, the next question is always “Why?” and then “What can we do about it?” 

That’s why so many marketers are investing in advanced analytics tools like Multi Touch Attribution and Market Mix Modelling. These kinds of products theoretically answer those questions, helping you guide effective decision making and uncover optimization opportunities. 

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.

Which is great, but only if these brands get a return on their analytics investment.

This is easier said than done. I’ve seen many organizations adopt advanced analytics approaches but fail to use the insight gained in an effective way. 

In almost every case, these brands want to improve ROMI (return on marketing investment). Yet as they proceed with their analysis, they often realize that different pockets of the organization have very different definitions of ROMI.

If everybody has a different measuring stick for success, as a marketer you will not be able to make many informed decisions. You probably suffer a perpetual state of indecision.

The good news is, we’ve seen this play out before, and we can help you through it. Here are five ways you can avoid letting your analytics investment languish – and turn your insights into powerful, profitable action for your organization.

Determine clear KPIs for the business and have the entire company agree upon them. This can be done by having open honest conversations about what the drivers of your business are. 

Hold everyone accountable to those KPIs. If there is no accountability, people will not take action upon results, leading to a lot of wasted resources. The Harvard Business Review has outlined five ways to hold people accountable: 

Clear expectations

Clear capability

Clear measurement

Clear feedback 

Clear consequences 

Train teams to accurately interpret the results. It’s crucial that your people must understand what the outputs are telling them in order to implement effective actions to drive business growth. For example, ROI is a simple metric that many marketers understand, but what they may not know is what is considered good/bad for an ROI. 

Bring together additional considerations to tell the full story. There is more to performance than just what the model tells us. A marketer should ask themselves why something is performing well or badly. For example, who was the target audience? Is there an opportunity to invest more into those tactics? What additional media was in market? Were there additional factors at play that could have influenced results?

Partner closely with your analytics teams. Unfortunately, I’ve seen many organizations in which these two groups work in silos, which results in marketers not always being clear on what they need, and analytics teams providing less than actionable insights. On the flip side, when the two groups come together, I’ve seen them come up with those Ah-ha! moments marketers dream about when starting their analytics journeys.

Only when all these factors come together can marketers extract the true value out of their models, as they will be empowered to make smarter business decisions. 

For example, a client of ours previously had a seasonal campaign running. Before it started, everyone, including the senior leadership team, came together to determine and agree upon the main KPIs.

We built a multi-attribution model to measure against the KPIs and trained the client and media agency on how to accurately interpret the results. Multiple stakeholders with different types of data and insights came together to discuss the results and it was determined that some creative messages weren’t resonating with their customers. 

Therefore, the company adjusted their creative in their media during their campaign. This resulted in a multi-million dollar increase in revenue, which more than paid for the models. 

In the example above, all the pieces of the puzzle came together to empower marketers to make smarter business decisions which drove more value for their organization.

It can be done – with the right help.

Originally published on The Drum

Lindsay Egan is a partner at Gain Theory

Most online ad experiences still feel like a re-run of last week’s searches and purchases.

We’ve been talking about how advances in digital media and data will result in every person on the web seeing a deeply personalized ad for every occasion since the days of AOL dial-up.

Why, then, do most of our digital ad experiences still feel like a “groundhog day” of what we searched and bought in the previous week? (If you don’t agree, just take a spin around the web and let me know how customized and rewarding your ad experience feels.)

Given the immense amount of personal data at our fingertips, you’d think that by now we’d be communicating elegantly with each customer—precisely when, where, and how they would like to engage with our brands. You’d think, with programmatic buying, that we’d be able to do this and still achieve huge reach.

And you’d think, with AI, powerful ‘identity graphs’ and multi touch attribution (MTA), that it would be easy to execute and measure these sophisticated conversations.

Yet personalization remains mostly a fantasy and right now it’s just not happening between brands and people. It’s time to examine why and to ask ourselves: Is personalization even a good idea in the first place?

Reality check
In trying to achieve one-to-one marketing, we might actually be putting our brands at risk of fragmented messaging, multiple personalities and vapor for brand equity. And even if we actually pull this off, there is a ton of mythology surrounding our ability to successfully execute micro-campaigning at the kind of scale we need to move markets and competitive share.

Often this comes down to simple math. If you target a specific slice of the web population using the powerful segmenting tools at your disposal, you may start with a million prospects. But, for every attribute you apply, you end up slicing that group thinner and thinner. Very quickly, you may find that your sophisticated marketing efforts have led you to a handful of shaving cream enthusiasts in the Pacific Northwest.

And we’re not even touching on the grand delusion that MTA can measure it all.

In our experience, working with even the biggest brands, MTA exercises are extremely complicated, expensive, require a crazy amount of work and rarely pay off.

It’s natural for CMOs to want to figure out exactly how every interaction with their brand leads to a purchase over a day, a week, a month and a year—and how much they should be spending on each media touchpoint to deliver that purchase.

But, in terms of practicality, it’s as big a fantasy today as “Game of Thrones”.

And here’s the friction…
Even if it’s possible to execute messaging with such surgical precision, there’s the small matter of whether consumers actually want to connect one-on-one with brands—even the ones they love.

In a YouGov.com survey from March 2018, more than half of adult respondents reported either neutral or negative receptivity towards personalized ads and the influence of such ads on their buying decisions.

We’re at a point where consumers are more savvy, empowered (hello ad blockers) and informed than ever. They are clicking permission check boxes and they are reading about EU fines for Google/Facebook and massive data breaches around the world. We haven’t even begun to solve the privacy issues associated with General Data Protection Regulation (GDPR) in Europe, while the California Consumer Privacy Act (CCPA) will soon be upon us in the U.S. Will identity graphs even be legal in the future?

The future is uncertain, but it will be bright
What we’re left with is a whole new world of ad targeting. We think consumers will end up in a place where they have far greater control and transparency around how they are being targeted.

They may even—wait for it-—agree to get paid by brands for their attention.
That may seem a little far-fetched now, but it actually represents a huge opportunity. Imagine a world where consumers actively engage in what they see and don’t see and they are actually “bought” into the relationship? Instead of wasting billions of dollars on unwanted ads, we will invest where ads are relevant and welcomed by those willing to be compensated.

It can’t get more personal than that.

Originally published on Ad Age

Chris Sloane, Senior Partner at Gain Theory heads up contributing authors in the Admap March issue which focuses around the topic of Frequency: How much is too much?

In his article, Chris Sloane looks at the history of frequency theory and what this can teach us in today’s media environment.

Below is an extract from the full article which can be found here.

Overview

In an age of multi-channel media planning, shorter consumer attention spans and ad avoidance, marketers and their agencies need to think hard about the issue of frequency when designing media strategies. Too little and the campaign risks having no impact, too much and advertisers are likely to be wasting money. And while it is true that even a perfect advertising schedule is not going to make an ineffective ad effective, it is also true that good scheduling can improve the payback of a campaign.

There has been widespread debate since the 1970s about whether a low-frequency, high-reach strategy is better than a high-frequency lower-reach one. This debate has intensified in recent years with the balance tipping towards the former approach.

In this article, we look at:

  • The history of frequency theory
  • What history can teach us today

Need to know

There are several points that media planners should be aware of when designing a schedule to invest their clients’ money, understanding these will improve and help to justify their planning:

  1. Can they make an estimation of the relative benefit of subsequent exposures? Various factors have the potential to make subsequent exposures in a given time-period more desirable, such as advertising NPD vs. established brands or levels of competitor pressure.
  2. Is it a seasonal campaign? For example, a retailer advertising at Christmas or Easter – multiple frequency in a short period of time is likely to be beneficial here.
  3. What is the degree of ad avoidance by media channel? The higher this is, the more frequency is to be valued. The level of ad avoidance by media channel should have an influence on how each channel is planned – maybe tight frequency capping for online isn’t always so desirable after all?
  4. What levels of advertising and brand recall can be expected for the message that is to be delivered? The lower these are, the more role frequency has to play.
  5. It is incumbent upon media planners not to have a one size fits all approach to their clients’ planning requirements. It is imperative to understand the nuance of the campaign, the brand and the category. Media planning in today’s world should be an exciting challenge, the evolving role of frequency makes it more so.

To read the full article click here.

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 

 

 

With over 20 years of experience in consulting, data strategy, technology and marketing analytics, Dodge will partner with Retail and Entertainment brands to support business growth from marketing investments.

Gain Theory, a WPP global marketing effectiveness consultancy that empowers marketers to create agile, smarter, data-informed cultures via data, technology and advanced analytics has appointed James Dodge to lead it’s North America Retail Practice from Chicago.

Dodge brings over 20 years’ experience helping retailers improve omni channel marketing effectiveness from within organizations such as Nielsen, McKinsey, BASES, Shure and Milliman. At Nielsen, he led the Retail Consulting & Analytics Team helping clients such as Lowes, Walmart, Safeway Albertsons, Walgreens, Roundy’s, Delhaize, CVS and Target, improve effectiveness with pricing, marketing analytics, forecasting, segmentation and customer profiling.  At McKinsey, Dodge was in the Retail Practice providing information, research and analysis on corporate strategy, store operations, branding, marketing, and CRM engagements for clients.  Most recently at Shure, he developed the corporate data strategy, started their enterprise data lake as well as a data engineering and data science team. 

The appointment of Dodge is testament to Gain Theory’s deep-rooted experience and commitment to helping Retailers understand marketing’s impact on both short and long-term business objectives. Gain Theory has been recognized for its Unified Measurement approach and the sophistication of their models. Gain Theory has also developed and successfully rolled out a groundbreaking near-term measurement solution called Sensor™ which allows for an “in-campaign” tactical view of performance across online and offline channels, without the need for Personal Identifiable Information (PII).

“I am excited to join Gain Theory at a time when many retailers require a partner that understands all of the complex questions they need answered and knows how to apply the right type of advanced analytics, data science and machine learning  for insights they can act on.“ says Dodge “Gain Theory is perfectly poised to deliver client success through speed, scale and sophistication.”

“At Gain Theory, we have a deep heritage in partnering with Retailers to address complex business questions.” says Shawn O’Neal, CEO North America ”I am delighted to have James lead our Retail Practice – his extensive Retail and CPG experience at the intersect of data strategy, technology, advanced analytics and consulting will add tremendous value to clients who need a data-informed approach to decision-making to drive growth”.

Gain Theory, the global marketing effectiveness consultancy that inspires marketing excellence welcomes Brian Suh to the global team. He will lead the consultancy’s Transformation practice, helping client partners align their organization around a disciplined approach to marketing investment management.

With this appointment, Gain Theory further underscores its commitment to delivering on its global mission of empowering informed marketing decisions, by more people more often. As such, Brian will be providing client partners with consulting services behind both Gain Theory’s solutions and assisting them in their journey of building marketing analytic capabilities. This will cover areas such as skill assessments, measurement approach integration and resource restructuring around people, processes and technology.

Prior to joining Gain Theory, Brian started his career at Deloitte Consulting and has since held multiple senior roles across OMD, Visual IQ, and Vaynermedia. His experience has seen him educate and guide clients on how to create more effective media and analytics departments within their own organizations. Advising on everything from technical topics like machine learning and data warehousing to more nuanced challenges such organizational structure and consumer privacy.

“We know from client partners that having the right insights is only half the battle when it comes to maximizing marketing’s value. The structure of marketing organizations and processes used to plan and deploy marketing investments directly impact the ability to improve marketing returns.” says Shawn O’Neal, CEO North America “I am delighted to have Brian join our team to help clients navigate towards a best-in-class marketing organization”.

On his appointment Brian says “I am excited to be joining Gain Theory. Marketers have an opportunity to generate sustainable business growth and having the right structure to unlock value from data and analytics is critical to help them succeed. The people and capabilities at Gain Theory are well placed to deliver this, and I am honored to be joining the team”

Brian will be based out of New York, Gain Theory’s North America hub and report to Shawn O’Neal.

 

 

Gain Theory, the global marketing effectiveness consultancy that inspires marketing excellence, has expanded its North America operation by opening an office on the West Coast in San Francisco, adding to existing hubs in New York and Minneapolis.

The expansion strengthens the consultancy’s partnerships with marketers on the west coast and underscores Gain Theory’s commitment to delivering ‘always-on’ marketing effectiveness programs for its clients in various time zones.

As a leading global marketing effectiveness consultancy, Gain Theory has experts distributed across North America, Europe, and the Asia Pacific servicing clients in 113 markets across a range of sectors.

“The decision to create a foothold on the West Coast was a logical step in our business growth and client support strategy” says Shawn O’Neal, CEO North America. “Some of the most sophisticated marketers in North America are located there and it’s critical that we meet clients where they live to service them most effectively.”

The San Francisco office will be led by Marina Stuefer, Client Development Lead. Marina has almost a decade experience in the advanced analytics field, helping organizations turn data into actionable insights, to help build sustainable business growth.

Over the course of her career, she has led multi-country client engagements in Fast Food, Retail and Finance adopting a range of techniques such as Econometric Modeling, Machine Learning and Test and Learn. Her counsel has helped clients understand their consumer’s brand interactions, optimize media mix and flighting, forecast multi-year returns from investments, understand business drivers and course-correct marketing activities.

“I am excited about the opportunity to strengthen our client development and support on the west coast,” says Marina. “It’s an exciting time for marketers and Gain Theory is really well placed to help navigate their journey to marketing excellence via the data, advanced analytics and consultancy capabilities we offer.”

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