Activating Success: Unified Marketing Measurement Best Practices

Featuring seasoned marketers, listen in as we explore best practices in data driven planning and activation.

Advanced unified marketing measurement and optimization techniques give more precise insights into the incremental value of marketing interactions, giving marketers a blueprint to guide future marketing investments. However, marketers struggle to turn these right marketing insights into action because of internal hurdles, technology limitations, or the changing advertising ecosystem. Marketers must adopt activation best practices like building actionable media plans and working more efficiently with agencies, to get the most out of their advanced marketing measurement solution. In doing so, marketers will extract the most value out of their optimized media plans and identify testing opportunities across audiences, channels, and tactics. 

Ipsos MMA, recently named a leader in The Forrester Wave™: Marketing Measurement and Optimization Solutions, Q1 2022 invites you to revisit our recorded webinar featuring Forrester Principal Analyst Tina Moffett who shares best practices in data driven planning and activation, and facilitates a panel discussion with leading enterprises sharing their experiences in activating successful marketing and media plans.

Don’t miss hearing first-hand experiences from:

Doug Brooks, EVP Global Client Management, Ipsos MMA

Tina Moffett, Principal Analyst, Forrester

Jon Francis, VP Global Analytics, Pay Pal

Mike Lau, Advanced Analytics Director, Commercial Ops, Gilead

Sean Barrett, SVP Marketing, Albertsons Companies


Today’s AI-generated audio transcript is offered below. Apologies in advance for inconsistencies that have been included.


Thank you for joining us for today's Ipsos MMA Webinar panel discussion sharing Unified Marketing Measurement Best Practices.


Today's discussion will feature a number of marketing professionals, and you can read more about them on the slide in front of you.


Throughout today's session, you will remain in listen only mode. However, throughout the webinar, you may submit questions online using the Q&A feature.


Time permitting, we will answer questions at the end of today's session. However, if time run short, then your question will be answered by e-mail.


Today's webinar is also being recorded and will be directly to you.


So now without further ado, it is my pleasure to introduce today's first speaker, Douglas Brooks, Executive Vice President of Ipsos MMA, Doug, You have the floor.


Hi everyone. Thanks for joining us today and for joining the panel discussion.


Before we get started, I just want to introduce the panelists and the moderator. So Tina Moffit from Forrester Research happy to have her today moderating the panel discussion.


Sean Barrett from albertsons, John Francis from PayPal, Mike Lau from Gilliard and this is Doug Brooks from Ipsos MMA.


As we go through the panel discussion, feel free to send your questions, and we will look to either address them at the end of the panel discussion or we will follow up via e-mail upon completion of the webinar.


So what are the drivers behind the discussion today? And what's, what's led us to this meeting today?


There are five key points that we will focus on, and they talked through as part of the discussion.


Anyone, whether it's ...


19 or many of the global market dynamics that we're experiencing today, what it has done is really accelerated the digital strategy of most brands across most global regions and more.


The media and commercial investment decision ecosystem is more complex than ever, and we'll spend some time talking about that.


The constant changes in both data and ad tech environment.


As many of you are aware of have really accelerated the need for a unified analytics to compensate for some of the data sparsity issues, the need for change management and true process workflow engineering to ensure that analytics are embedded and activated effectively through a closed loop process. Then, from an organizational standpoint, all of this is culminating.


We're seeing the role of CMO's evolve into more of what we would call a Chief Commercial Officer for both omnichannel and cross functional business planning.


So, if we think about the complexities of the commercial decision making ecosystem, this is what it looks like for many companies, whether your financial services, apparel, retail, restaurant, Telco, pharmaceuticals, right.


You have this very complex matrix of audiences, whether you're looking to acquire new customers and grow lifetime value of existing, competing against many, the players in this space for, this is your share of voice against those audiences.


Tactical execution, understanding the right allocation of spend across platforms, and ad formats, and placement and timing.


Channel and platform Mix.


Really, one of the true key themes today is around the balance of Brand versus Performance, synergy's, understanding, not just how activities may work in a silo, but how they work together in an integrated manner.


Then finally, the impact of market conditions.


Being able to make all of the just these decisions, while understanding the implications of changes in marketplace dynamics, whether it's gas prices, or, or global economic factors. And how they would influence the effectiveness of your strategies in market, and the behavior of consumers.


When we talk about the changes in the data, in the ad, tech environment, right? So it's everything from looking at the loss of third party cookies, right?


Walled gardens, fragmented data is loss of loss of identifiers, the explosion of retail media networks, right, another option in the media mix, and another opportunity around targeting.


All the way through to identity and first party data.


Understanding the rise of permission based, first party data, or see the peace across many organizations. Then, to add to the mix, growth in connected TV as another option, And we've seen that significant growth over the last few years.


All of this has brought the need for this unified marketing measurement capability. And this is what we're talking about today.


Unified marketing measurement is really bringing together. the value that a marketing mix approach brings, which is holistic.


Looking at brand media, performance, media, CRM, things like sponsorships, Salesforce, and bringing in operations factors, and external factors to control for them, Linking that to an attribution model, to give you that in real-time, targeting activity against customers, audiences, placements, et cetera.


All of this through closed loop framework, that allows you to balance short term and long term.


Optimized investments support both annual budgeting in real time, while also controlling for these external factors.


The change management computing component of this has never been more critical.


As you've seen from the previous charts and the parts of this discussion. It's not just about marketing and media. It's about the integrated operations and business drivers and external.


The need to bring the entire organization along for the journey.


Right Gagne, cross functional buy in and alignment driving effective activation to purpose workflows.


Are you tracking an ongoing validation? And then having a formal marketing, re-appraisal and re optimization process as an ongoing feedback loop.


And that brings us to the evolving role of the CMO, as, as we've talked about, with all of these different components around integration across functions, bringing different, disparate data sets together, bringing different forms of analytics together, bringing down silos in an organization, so that you plan and optimize commercial investments in a unified way.


The chart to the right sort of tells the story around the dimensions of managing customer strategy, global markets, Trying to drive growth and margin, bringing together a marketing strategy with a product strategy, a customer strategy, and an overall unified strategy within the environment of changing external and competitive market dynamics, the role of global portfolio, omnichannel strategy, business planning and scenario planning, accounting for external changes, and then cross functional centers.


So, let's dive right into the discussion. I'll hand it over to Tina Moffet now to lead us through. It.


Really focused on how are these industry leaders addressing the challenges that I just addressed, what forrester's seeing in the marketplace? And then we'll close with what is our point of view over the next 2 to 3 years.


Great. Thanks, Doug.


And thank you to the MMA team for inviting me to moderate this panel of really impressive marketing and analytics leaders today. And I look forward to a lively discussion. So, as Doug said, marketing school, really, its mandate, is to help build long term, sustainable business through smart acquisition strategies, and continued growth, and retention of existing customers. Now, to do this effectively, marketers need to embrace it in analytics. Specifically, what Doug just talked about, Unified Marketing measurement, which is the orchestration of advanced, analytical techniques to understand strategic and tactical marketing efficacy.


And that approach uses data to understand what marketing is working, what isn't, and to really give marketers a blueprint to develop data driven marketing plans.


Now, this requires a lot of alignment of people, process, data, and technology, and insights, and analytical expertise for more precise measures, but it doesn't stop there. The insights, you need to be practical, widely adopted, accepted, and ultimately, actionable, so marketers and agency partners can take these results and build data driven marketing plans. So, marketers need to apply best practices to ensure these insights are accepted, adopted, and activated. And we know through Forrester Research that one of the top challenges with using more advanced marketing measurement approaches, like unified marketing measurement is issues like stakeholder buy in, and activation of insights. So, I'm happy to be here today, with our panel of experts.


Will discuss their experience in using Unified Marketing measurement, and they're going to provide some best practices on how to successfully adopt and activate insights from the Unified Measurement Model. So, let's get started with some really great discussion.


My first question is really around the changing tides, right? We're seeing a lot of major economic, environmental, and advertising ecosystem changes, that force marketers to shift their marketing strategies and overall plans.


Marketers now need to consider how forces like inflation, the pandemic, third party cookie deprecation, and even supply chain issues will impact their overall marketing mix, the performance of their marketing, and build these considerations into their marketing measurement models and their future marketing plans. So, Sean, I want to start with you. As Marketing Leader at albertsons.


You see that the grocery, industry CPG and even kind of overall retail, experience economic pressures, specifically supply change shortages due to ..., How do you consider the changes in the supply chain due to ... in your marketing measurement and optimization models? And how do these market forces, how have they shifted your marketing and media dollars at albertsons?


Great, great question.


Good to be with all of you on such an important topic, this morning.


Yeah, it's, I think that what you've described, and certainly what the grocery industry, but many other industries have gone through over the past year. It's just an incredible volatility. There's been a ton of uncertainty in it, and it's been volatile, obviously, from the effects of coven and everything that has happened since then.


The supply chain constraints it we have today and the inflationary environment that we have today.


But, also, as most of you know, I mean, it's just a fascinating field that we work in, because it's changing every day, Some of those changes are positive, and some of those changes require us to react.


So, you know, I see, I think, the key to, yes, at succeeding in this, is agility.


And agility is significantly aided when you have confidence and in measurement, and when you have an approach to measurement, that gives you confidence in results, and what's happening that, you can used to react to on a variety of different levels, at a macro level, for maybe making significant budget shifts. Or on a micro level of optimizing performance on a daily or weekly basis.


I mean, it's specifically for albertsons in grocery right now. Yes. As you mentioned, there's supply chain constraints. Which many industries are dealing with, but also inflation that's hitting our customers significantly.


And grocery is an incredibly complex business.


I mean, we have thousands of thousands of deals in our stores every week on tens of thousands of items that we stock in our stores. So, you know, what the key is, is delivering the right message and the right deal, and offer to the right customer at the right time.


That incorrect requires an incredible amount of personalization.


So that we can bring the best deals to people, so they can stretch there, budget, as far as possible when they're coming in to make their grocery shop.


And, of course, you know, with supply chain constraints, we have to make sure that when we're offering a deal to a customer, that what they see in our advertising, they come into the store, and they get, or it's a completely wasted impression and waste of advertising dollars.


So, the key to that for us is just great, great.


Data, foundation, great, personalization capabilities, and, and, you know, the ability to optimize dynamically on the fly, and also, you know, on a near real-time basis, looking at measurement and impact and shifting dollars and focus.




Now, John, at Pay Pal, I know you probably have to deal with a lot of changes that's occurring in the tech industry. Now, specifically with the third the Google's intention to deprecate, the third party cookie and even Apple's restrictions on tracking within their ecosystem. Now, Pay Pal as a leader in the digital payments space, I'm sure has felt that impact. Can you describe how the changing ad tech ecosystem has impacted your marketing measurement and media measurement models and optimizations?


Yeah. Thanks. Thanks for having me. Really excited to join here for the topic.


And, you know, I really like what what Sean said, as well around consistency And building a strong foundation, because I think at the end of the day, the Shifting Sands have changed our perspective just in terms of the measurement Rubric and and how we understand the efficacy of how we're deploying dollars.


And, you know, what, we've heard loud and clear from our marketing stakeholders and like, it's not just pay pal.


It's not, you know, this isn't a unique problem that we have the same challenges at Starbucks.


But, you know, we we, I think there's an element of sausage making and trying different measurement techniques over the years in different disciplines.


Or how you do it, and then some cases where, measuring a program with two different methodologies. And if you ask any marketer, right, to pull their hair out.


Because we spend a lot of time just trying to adjudicate what maybe two different approaches let's say.


So, right now, there's more and more of a push for simplicity, and a clear rubric for how we think about measurement.


And, I think that's where the power of, and, I promise, this is an applied for, perhaps, ask, but, just for how we think about the framework, and especially on the media mix modeling, which is really where we think of as a single source of truth, for those higher level investments and where we deploy dollars. Because, by the way, as you mentioned, it also affords us the opportunity to account for.


Other factors are covariance of things that can be an influencing what's happening to our cells. Because it's really a multivariate approach to solving when it's truly a multivariate problem.


And that's the advantage over what we may have historically done with different types of measurement solutions where it's sort of like, you're, you're looking at a part of a problem in isolation when you really want to be looking at it as a multivariate solution. So, I think that's really the power here.


And I think it's really helping our marketing stakeholders understand and, you know, really just know that they do have more than one stop shopping for the higher level understanding of ROI, and, you know, where we're deploying dollars now, when it comes to optimization.


Of course, MMM won't work, but that's where we rely more on where we can no leverage experimentation and testing, especially with our own channels, where you can actually start to test and learn against whether it's different versions of creatives are different types of targeting or segments that you want to go after.


Using them, the incrementality, in the experimentation capabilities there, to help inform that tuning and optimization, that was relying more and more on the unified measurement approach with them, to help us kind of inform how we're thinking about higher order investments.


I think knock on wood, that approach will hopefully be future proofed.


In terms of how we are seeing some of the changes in the industry and it will allow us to keep kind of a finger on what's happening from an efficacy perspective and, and I think the consistency, as I mentioned and Sean mentioned, it's important, because I think that's really what our stakeholders are craving.


And they don't want to hear about some whizzy weg, new application for measurement.


They want to see something that's repeatable time and time again that they can understand, and I think that's the value here.


I think what's really interesting, you mentioned testing, for sure, we administer a Global Marketing survey every year since, I mean, there were Forrester for about 11 years.


And we asked question about methodology for measurement and we saw a, an 11% increase of adoption of testing and experimental design as a way to measure uplift, right?


And I think it's like addressing the issue of us on a day to day, campaign, and tactic reporting, we need a better way to measure incrementality. So, and what's old is new again, I mean, 15 years ago, this is what we used to do.


On the client side.


So, Mike, on, from your perspective, know, you have your, in a very, very interesting industry, being a party juliane, where you have multiple objectives, you may have multiple constraints, and you have to address the needs of, and patients and physicians, right, because they're both your customers.


Can you describe how an event like covel has impacted your marketing analytics, and measurement approaches? What did you have to now consider, because of ...? And then, how did you accelerate your overall digital strategy?


Yeah, absolutely. Thanks for the question, Tina. And thanks for having me on this panel.


I think it's really interesting hearing from these other panelists, across industries, because so much of it still resonates despite the differences in our businesses, which is, which is amazing to hear.


But to your question, you know, historically, Pharma marketing has been very reliant on the impact of our field, Salesforce, going to, the doctor's offices, talking with physicians, communicating the value proposition, The, Target Patient profile of our, of our products.


And I think that, you know, all the other channels that we deploy, you know, TV for, for direct to Patient Marketing, or Digital, or, Social, really plays a subservient role to, to bolstering that personal promotion via that, Salesforce. And, so, for obvious reasons, once ... hit us in 20 20, it really forced us to re-evaluate how we thought about our overall marketing strategy and approach across all of our product areas.


Specifically, because so many of these healthcare providers were overwhelmed facing ..., and they didn't have time to have us on-site, talking about products that are unrelated to, you know, what was, in their mind, the most urgent need and fairly so, rightly so. It presented us with a challenge, right?


How do we continue to drive our business, continue to engage with our health care providers so that other therapeutic areas And patients in them continue to get connected to care.


So we had to play catch up in many ways to other industries and to accelerate our digital capabilities.


And that came with increased investment and a better need to understand the impact of those digital campaigns and performances and how it was connecting to and driving our business overall.


So we ended up expanding our digital marketing operations team.


We increased our investments in Non-personal promotion tech infrastructure. We expand our analytics capabilities with unified attribution.


So we could have these near real-time optimization capabilities with our media agencies, And even as covered restrictions, have East. It's clear that this is sort of the new normal for us, right.


It just took something as biggest cobie to really kick in the pants and get us moving in the right direction to start catching up with these other industries.


But I think this is definitely the right way to head in terms of the future for our digital strategy.


Well, you know, what's interesting is that at Forrester, we've been tracking for years like the shift from traditional media to digital.


And when the pandemic happened, it just just we saw more dollars go towards digital. And we were like, this was the pendulum that finally swan Digital Investments to increase over kind of traditional media.


And I think, across all industry and we saw that across all industries, and it was even accelerated when we saw through our Consumer techno Graphics Survey that, you know, people were, we're shifting to at home working. They were online more. They wanted to engage more. And they eventually started a hunger for, like, going out and going in store, but I think marketers did a really good job at identifying and shifting almost immediately towards digital investments. Great.


So, I think, I think I want to shift the conversation a little bit to understand your point of view on, on some challenges.


Clients we talked to in our for 2022 Forrester Wave Evaluation Process for Marketing Measurement and Optimization Solution indicated that a specific challenge for marketing measurement adoption is stakeholder buy in.


And this is really interesting to me because we talk to c-mos all the time and they, they always say, Hey, we are data driven, but according to our data, we're hearing, hey, it's really hard to get stakeholders, to have to get consensus, and confidence, and a lot of these analytical models. I want to explore some best practices across our panelists, and what are some best practices that our panelists have used to secure adoption and confidence of, of their unified marketing measurement approach? So, John, I'm going to start with you. ..., PayPal, you've had several senior analytics roles across other industries, including Tailcoat QSR, according to my, my research to prep for this call. I did a little digging on LinkedIn.


So what are some of the universal best practices that you can, you know, share with us in gaining confidence and consensus among your peers?


If you're kind of building this very sophisticated unified measurement model, and how do those best practices change if you have different organizational structures?


Yeah, like, I mean, this could probably be a subject of its own webinar.


And, you know, I'll admit openly a lot of failures along the way on my learning journey.


And I think it's, it's probably have, I probably have tried to overcomplicate it too much in the past and so I've pivoted pretty hard over the last few years.


But I think one observation, regardless of whether it's marketing measurement, or any other analytic data product, it's not a field of dreams.


Meaning, if you build it, they will not necessarily come.


And, and I think Doug talked a lot about the change management and his, his opening, and I could not underscore the importance of that and how you think about bringing people along on the journey for adopting these new tools and capabilities.


It's not about having the best AI or machine learning or the smartest ... model. No one cares.


It's about actually having the empathy and understanding of what the marketer is trying to do and deeply immersing into those needs and and frankly even just showing that you're willing to roll up your sleeves and partner on how you can use data to to evolve the strategy in being really viewed as a credible partner.


And not someone who's trying to keep score, how marketing is doing, and saying, well, I like you guys.


You guys really suck here, Or, this was really bad. Now, it's not about that.


It's about creating a culture where of empathy and understanding, and looking at what the data's telling you, and how you can evolve those learnings. Not just from a dashboard or report where you share how everything was working, but you actually have a seat at the table, and you're making recommendations based on the data.


Is saying, I think that there's a high degree of credibility, and a lot of times you see missing and an organization's analytic organizations where it's more well, here's what we observed.


Here's the Dashboard. You can go check it out.


And that, that model. never works. And so I, there's a lot here just around mindset. I think that's a big part of it.


Then the other is just as you think about capabilities within your team.


My other learning or Aha, is the idea of these analytics strategists.


So, folks that can partner closely with our marketing organization, And they're going to be, you know, again, a seat at the table. And they can help.


Really, with the change management.


And how you start to create a roadmap for how you can evolve the learnings, and the tools that are being stood up, and really start to test and learn and to that.


Because my other observation is, and again, back to the field of dreams comment.


If you just drop a new capability or tool on someone who's been doing a certain job for a certain way, for years, chances are that they're not going to immediately organically gravitate to it. Because they've already got a full plate.


And, you know, 8 or 10 hours a day are already trying to scrape buy in, in terms of what they're already doing. So, you have to be very intentional about the change management, how you bring people on that journey.


I think, I think that's probably, again, and some ways that that capability, or that mindset, is probably more important than the tool itself, And so, I think you've got to find the right people in your analytics organization, who can, who can help with that. And that's not an organic skill set that comes from from a data scientist or statistician.


I'm sorry. I completely agree, now. Mike, you mentioned ..., you have to co-ordinate between marketing and sales team to gain confidence and support of your marketing measurement and optimization models.


I know that, for sure, as analysts, I often talk to similar industries, like insurance, where they have the same problem, they have to co-ordinate between marketing and agent teams to kind of ensure marketing efforts are being used and tracked. So, what are some best practices for adoption of, like, a unified measurement model across these different functional groups?


Yeah, I mean, I think that one of the great opportunities of unified measurement and marketing mix is also the greatest challenge, right?


That it's not a single stakeholder that you need to get on board.


These are comprehensive models that span as many channels as you can have data for.


And what that means is that there's something in it for everyone, Right?


Whether that's your sales leadership, or your physician promotion team, or your patient promotion team, They each have a stake in those insights and the results that we bring forward to the executive team.


And, as a result, you need to work intimately with each of those functional groups to really educate them on the methodology, get their buy in, get that credibility built that John was talking about. Really collaborating with them, right? So that they're in it with you, they feel ownership.


You source their data, you understand their key business questions, you understand what they're trying to accomplish and what they're trying to get out of this readout, right?


It's not just a grade, you know, you scored an A, or A, B, or C, It's, you know, this is where you did well, This is recommendations for improvement, This is what you were trying to achieve, This is where you did or did not, and how you could, you know, really work with them to understand where are these models can play in terms of serving them, in terms of giving them a path forward.


And so, they're getting something out of it, as well as you are.


And we've found success by ensuring that we're not just including folks at the leadership level, right?


We actually want to get down and dirty with the product managers, with the agency partners, so that we can establish that credibility and establish that collaborative relationship to really help those diverse functional groups feel this sense of shared ownership over the outcome of analytics.


And then, as a result, the insights, right? At that point, it becomes an organic extension that they're going to take those insights and run with it.


You don't need to force that upon them. Right? They were there building it with you, and they were the ones asking the question.


So when you help provide the answers, you know, they're going to take it and run.


And I think, you know, finally, you know, for those of us that have multiple product areas that we're supporting, really find one that you feel like you have a high probability of success with.


Establish that, you know, the relationship really nail it and then leverage that relationship across other product areas as well.


Right, Use that as a shared experience, excuse me, a shared experience to really bring others on board.


Great. And, Sean, can you give us, if you could give one best practice to people attending, on how to build a confidence with confidence and acceptance of your unified measurement model within the C suite, Specifically with the CFO team, what would it be, what would be that one best practice?


Ah, have to do one.


That's just a couple of comments, because I thought Jada, Mike, both, it's great comments.


I think that, you know, Jada, uh, you know, one thing that I just want to echo is just a culture of learning and being data driven. It's just critical for your company to embrace.


And the more that starts at the top, the better we've been on that journey and, and are much more of a culture of wedding data, inform our decisions. And we were several years ago, so I wanted to reinforce that a culture of learning and putting the data at the center is critical.


And Mike also mentioned enrolling others in the process of developing your marketing mix model. We've found success in that as well.


Watson, we operate in a number of regional divisions and collaborating with our Division teams to make sure data that we have for what's going on in their market is accurate, is critical because garbage in, garbage out is the easiest way to get your model thrown out the window when you're trying to enroll stakeholders.


So, my to tip tips, additional tips for enrolling your, well, and, you know, just confidence in a marketing mixed model and return on investment is like the most important thing a marketing leader needs to do. If you don't have that, you don't have anything. And if you don't have a data source and a proper measurement methodology that gets you there, you're starting from a really shaky foundation.


And I've found that your finance team is one of the most important partners in this.


And, and what, and one of my tips for working with the finance team is, it's about, you know, roll up your sleeves, education, and persistence of, you know, running through it in whatever detail is needed.


Because a lot of people don't understand the very complex methodologies for marketing, mix modeling and regression based analysis. Your finance teams are the most likely to get it, but they still will need to roll up their sleeves and really understand it.


So you just need to take that time and do it over and over and over again until until people can get the input and feedback and feel like they fully understand the process. So, that's one.


The second thing I would suggest is doing test and control experiments, and showing impact, and then connecting that with impact from your marketing mix model as well.


People really can sink their teeth into test and control experiments and it's a really great validator of what you're seeing in your ....


Great, thank you.


And, and before we move on to our next question, I just want to encourage anybody who has any questions for our panelists, or for me or for Jogged, these just pop them in to the Q&A portion of the, of your control.


So, another challenge we discovered is activation, I know that for sure this is always a challenge when we ask the question, What's the biggest hurdle of making use of your measurement and insights? So, he's around data and then activation. It's it's a herculean task that requires a lot of co-ordination between internal analytics teams and marketing leadership teams or even director levels of marketing and media agencies. So I want to dive into some best practices around how to activate a lot of the optimization recommendations and scenario plans. So, Mike, I'll start with you. I know you manage a lot of moving parts at Juilliard, and to ensure a consistent portfolio view of marketing performance is not only shared, but it's actually acted on How do you ensure and continually manage the recommendations from your scenario plans or your optimization models?


How do you ensure that they're activated across your internal teams, like sales and marketing, as well as with your partner agencies, and how you connect those dots dots between the agency partners and your internal teams to ensure that workflow is consistent?


Yeah, absolutely. I think from an internal standpoint, it really starts with what we touched on before. really engaging the stakeholder groups in the beginning, making sure it's a collaborative exercise in building that sense of ownership, and co ownership with them into the insights that they're looking for.


And if they come into it with a specific set of questions that you can uniquely answer with these models, you don't really need to hold them accountable to activating on them, right? To sort of do it themselves.


But beyond that, I think, you know, what we tried to do is really think about how timing of these analyzes and timing of these insights matters. Quite a bit, right?


We plan and schedule our marketing analytics to readout to coincide with our annual brand planning process.


And that way, those insights are delivered in a timely way. That can be immediately built into the upcoming brand strategy and tactical plan for the upcoming year.


The models we build for scenario planning or budget optimization can be used directly in budget requests and expense planning. And things like that also coinciding with that timing of the year.


I mean once you have that cadence worked out in that working relationship established, the pull through on insights and recommendations becomes much more organic, right?


And you know I think that one thing that we do really well with Ipsos is ensure that we have partners with, with the agencies as well, partnerships with the agency on a monthly basis with those optimization readouts.


So Ipsos works directly with the agency. They sort of co develop action plans based on the insights that that they see in the data.


And use those monthly check ins as a mechanism to keep their eight and you know that to keep the action Plans active.


And, and refreshed, and our brand partners really use those as opportunities to hold their agencies accountable.


So, using that, that credibility that we've established allows us to be their eyes and ears to provide that unbiased view of performance that they can utilize.


And, most importantly, they can track the impact of those optimization decisions, which further reinforce the importance of analytics and the benefit to both the brand and the agency teams.


Great. Now, Sean, you manage several large local brands across country, and because of this, you have managed various analytical needs of different marketing groups. And measurement and insights could look very different across different brands and demographic areas. And I can imagine that managing activation strategies across different agencies and internal teams, at a local level, would require a tremendous amount of co-ordination across your workflow. So, how do you ensure that your marketing measurement optimization recommendations are activated across hyper local markets while meeting the needs of different internal teams and dealing with different agencies?


Yeah, Good question.


The, you know, a couple of things I'd echo that, Mike mentioned, is your agencies have to know that, and your, all, your partners, in good marketing need to know that you have a single source of truth for performance, and that's your marketing mix model, and ultimately, any recommendations I get from an agency have to be anchored in that.


And all of our planning and budgeting discussions have to be anchored in that.


Mike also mentioned, coinciding your redoubts on your model with the planning cycles.


That's a great best practice and the planning should start and end ultimately, through forecasting with what your marketing models are predicting and expecting from the performance.


Now, we do, at albertsons, manage over 20 regional banners.


And we operate with 12 regional divisions to do that. But the the marketing is not as complex as it might seem.


Most of our digital media is managed at a national level.


But what we work with our local partners on is localizing the messaging. So we leverage our marketing mix model to plan and budget on a local level. But if we do that right at the beginning of the year and we revisit it quarterly, we pretty much stick to that plan.


Then, the work becomes optimizing and making sure that the messaging is right for each of the local environments, and specifically that we have continuity between our messaging across all channels. So, if something is happening in one of our stores, that it matches what we're doing in digital media and other places as well.


Millimeter, hm, great. And we're coming up close to time, and this has been such a conversation and discussion. So, I actually want to skip to the final question. The advertising and marketing ecosystem will experience drastic changes over the next 2 to 3 years. We're experiencing it now, and I want to get all the panelists opinions on how they expect their marketing strategies, and data measurement, and planning initiatives to change, given the changes in the advertising and marketing system. And, John, I want to jump to you first over the year. So we anticipate that Google will deprecated third party cookie.


Cookies and walled gardens will grow higher. We already see it with different publishers and retailers, building, ecosystem, their own ecosystems. And this is going to be making for more challenging to measure cross-platform Omnichannel advertising strategies. How do you think this will shake out in the next year and how your How are you preparing your Pay pal team to address these challenges?


Yeah, I think keynotes well. What we talked about before, I think the good news here is, or, maybe, it's bad news, I suppose, but, what, you know, what we learned through the changes from Apple.


And, in terms of, you know, what, what's happening with third, third party data and cookies, informed our current decisions, and how we're approaching and putting more emphasis on things like the Media Mix Modeling.


In terms of how we think about measurement, I think we'll just continue to focus on that.


And then as you think about more Local Optimization at the campaign level, it comes back to just continuing to lean in on, on own channel, first party data, experimentation, and test, and learn, to help inform where you can and get those incrementality reads. So, I actually think it's just a continuation.


The strategy that we've already put in place, and, you know, in some ways where we sort of know, it's a bit of a firewall around the changes Google is making just in essence, because of what's already happened with Apple.




Now, um, now, Sean, in your industry ecosystem, how do you anticipate the rise of the retail media networks impacting marketing and media analytics at at albertson's? And what are you doing to prepare for this shift of media within the media selling and buying ecosystem?


Yeah, it's a great question. I know we don't have a lot of time, but retail media networks is a big focus for us.


We actually, I launched our own retail media network this past February, called Albertsons Media Collective.


And that was the result of a few years of hard work, bringing our marketing technologies up to where they needed to be, to be able to deliver a great product to our CPG partners. I was a former CPG marketer.


And I believe that, you know, if if retail media networks had been invented when I was working for Procter and Gamble, I would never have invested a single dollar that I could be tied to a proven transaction. I really do think it's that it's the future of where media is going. There's still a lot of work for the industry to grow up, but ultimately, marketing is about selling something.


The companies that do have, that, ultimate transaction data, if they can build a proposition for their vendors and suppliers to advertize and close the loop on on performance. It's a game changer, and, you know, ultimately, it's gonna make you a better marketer for your enterprise marketing as well.


All of our enterprise marketing runs on the same rails in technology as our Retail media Network, and we measure and optimize the same way, making sure that everything we do, We look at the transactions that result from it and optimize for maximum ROI.


Yeah, I think it's, I think it's super interesting, the retail media networks, because, to me, it's not only about the opportunity to connect directly with the retailer and an advertiser to measure and target, but there's implications of, like, using that data to understand, like, market basket analysis and consumer behaviors.


So CPG companies, I know are just foaming at the mouth for that information and now they have at their fingertips. Which is really exciting. It's, it's a massive shift, I think, in the, in that particular industry.


Now, now, Mike, I know, within your industry, you leverage a lot of patient and doctor Data Toute measure and manage marketing and media initiatives with the spotlight on how marketing and advertising and the advertising industries use data.


How do you expect data usage for marketing, measurement, insights, and planning purposes to shift over the next two years, and how do you anticipate your data investments to change to support that data driven marketing planning?




I think, um, broader privacy concerns over consumer data will certainly spillover and impact how we use these tools to resolve the impact of our marketing investments.


Pharma, having, you know, dealt with are dealing, Not Tell has been working within the environment of HIPAA compliance. Means that we may actually be ahead in some respect, right, in that our data already needs to be sanitized tokenized to meet HIPAA compliance standards, which are fairly strict protections and patient privacy.


So we have experience, you know, working within constraints and still getting to the degree of insights that we feel we need in order to make informed decisions.


But that said, there will obviously be ever more focus on technology and data solutions that help to mitigate that loss of data granularity that we expect to see without necessarily losing the quality of the insight and actionability of those insights.


At Joliet, you know, talking about the next 2 or 3 years of Data investments we're putting a lot more focus in our ability to connect our marketing efforts across channels seamlessly right, via omnichannel. I mean, this goes back to the first question on how our data strategy or a digital strategy is starting to mature.


And so, one of the challenges there is really trying to marry the data from these different channels, and sources, so that we can model next, best engagement, and execute a more personalized, dynamic, relevant, targeted, campaign.


And we're certainly not there yet, but that's, that's what we're building towards, and that's where our focus is going to be.


Great, and I actually want to direct my last question to Doug. You know, Doug, you have the unique and good fortune of having a multitude of clients across across industries, you know, the vendors in this space of Marketing analytics and measurement are on the cusp of understanding what is happening in the future. So what do you think the next 2 to 3 years is going to bring given your knowledge of what your clients are going through and what you understand about different industry needs?


Sure. That great question. Yeah, it's gonna be all about the constant focus on evolving the analytics to find the right balance of probabilistic or model based approaches with deterministic 1 to 1 approaches, to fill in the blanks, a data sparsity, right, that's created by a lot of these changes in the ecosystem. That's one.


The other big trends that we're seeing out there is accelerated global scale, being able to do this consistently across multiple markets, so it's comparable. And you can learn from it.


The third area that we really focus on a lot of companies is the is a move towards closed loop.


So integrating things like testing and ongoing testing, and validation processes, and activation processes into this.


And the last point I'll make is that, you know, with what we've heard across between Shaun and Mike and John.


It's this move towards integrated analytics, right? So it's not just looking at marketing. It's bringing in things like pricing, analytics, and business forecasting, and testing and other forms to have a more holistic view of the business. So, yes, but that's what, that's what we're seeing today. And that's where we think it'll continue to go over the next 2 to 3 years.


Yeah, and from my point of view at Forrester, I think that we're seeing kind of a need for simplicity, which was mentioned earlier.


No. Demand for transparency, and transit transparency into these models. And when I hear the word transparency, marketers really mean like, I just need to understand what's going on. I don't need to kind of dive into, like, explanatory values, and why things, like you just need to understand what's going on.


And, Doug, you mentioned, and we completely agree, this notion of inclusiveness of other functional insights, And I think that was accelerated by coven, right? So we started hearing a lot of CPG and retailer has started to consider demand generation, inventory availability and then shifting their media flighting based on those two.


I think, I think, covert accelerated that the more co-ordinated what we call that forest or insights driven approaches as well.


Yeah, Great. So thank you, everybody, for attending this session today. We really appreciate it. We have two questions that I want to try to see if we can tackle before we close out. And this one is directly to John. John, how did you know when you were at the tipping point of gaining organizational buy in and traction with your unified analytics program?


Yeah, it was hard fun.


Let's just be clear night. And I think Sean me may have said it, just the idea of educating, educating, and educating.


And I didn't know what the marketers say that you have to say something seven times before it sinks, and there was a lot of that.


But I think the moment that I actually knew we're breaking through was when we were, we stop pushing in terms of, hey, here's the latest quarterly or semi-annual results of where we're at with our media mix model.


And the marketing team was asking and where I would see the ROI reflected and their business case to go get more dollars.


And so I think for me, it was, it just sort of got woven into the vernacular of the team and how they thought about the strategy.


And, and so I think my like I said that that was a long journey.


Again, going back to the point of leading with empathy, deeply immersing yourself in what the marketing team in the business is trying to do.


Understanding the challenges of how they did their work before and how what we're trying to propose with the new framework and rubric would help them. It was all that.


So I think the maybe the other thing I would say is the thing I underestimated was, and Doug was on this journey as well. And Starbucks was the data side of it in the data journey.


And the amount of the shure heavy lifting, I've even doing one cut of the models, and, and I think we got better over time, but I think the more that that can be streamlined.


An automated and create discipline where it's not a big, monumental effort to rerun or update the model on a semi-annual or quarterly basis.


But that can be automated.


I think, if, you know, turning back time on Starbucks, I would have invested more resources there, to help in that space, because if it was, it ended up being just such a huge lift and every time we wanted to look at it. And so I think that maybe there's another journey that, you know, maybe best practice.


Don't underestimate the effort of the data collection and integration to to bring the modeling the life.


It is that is the number one challenge. After year, when we ask the question, what prevents you from using or what's the biggest challenge with marketing measurement optimization? Is data data, velocity, data quality, managing multiple data sources? Next question to Sean before we close out, how do you balance competing priorities of brands and markets when rolling out a unified marketing measurement program?


It's a great question.


The worst I'd say, we're still working on that. honest.


Because, historically, the way we budget and plan is on a regional basis which has hindered our ability to necessarily fully optimize our, our marketing investment.


Because when you're P&L was managed in regional budgets, it's hard to flow dollars from one marketing budget, P&L to another as fluidly as you bite, within a market. So honestly, we're still we're still managing through that.


And actually, the data and marketing mix approach that we're using is the number-one lever for opening up that as an opportunity. And now we just need to figure out how to tackle it.


Great. Well, I want to thank my panelists for sticking with me for about 40 minutes to have this lively discussion on best practices for adoption and activation of a unified marketing measurement approaches. Doug and the MMA team, thank you for inviting me to moderate this panel. And I'm going to send it back to Allen, where she's going to close out the session.


Thank you, everyone. Thanks, Doug, Tina, John, Mike, and Sean for today's really engaging and interesting discussion. And thank you, everyone, for sticking with us. I know we went a bit long. You will be receiving an e-mail with a direct link to today's recording presentation, so you can revisit all the great insights that were shared. Of course, in the meantime, at anytime, we welcome the opportunity to speak with you, so please reach out to us directly.


That now concludes today's webinar. Have a wonderful day, everyone.


Thanks, everyone.

Consumer & Shopper