The AdTech industry is undergoing rapid changes as it adjusts to the impacts of data deprecation and ever-changing privacy regulations. At the same time, there are fears of a potential economic downturn. How should you handle marketing in a recession? What should your marketing mix look like? In this blog post, we’ll cover how to navigate this uncertainty and three essential ingredients for your marketing mix.
First, we’ll look at the complexity and uncertainty facing marketers.
Turbulence with Twitter
After Elon Musk’s Twitter takeover in October 2022, half of Twitter’s top 100 advertisers left the platform and started to seek out alternatives.
The retail media boom
In the next four years, Forrester Research projects that U.S. retail media ad sales will double to reach 85 billion by 2026.1
Most of this growth is catalyzed by CPG and consumer electronic brands that have a scarcity of zero- and first-party data; they need more media closer to the point of purchase, especially as CFOs are scrutinizing budgets.
Consumption continues to fragment
It’s becoming harder than ever to reach the right person, at the right time, predict their intent, and get a 360-degree view of your customer.2
Data deprecation is top of mind
According to Forrester Research, updating their data strategy to address data deprecation is the number one priority for marketers. Addressing data deprecation is also a priority for consumers, who increasingly feel that audience targeting is more intrusive than beneficial.3
Data deprecation affects identity solutions
Third-party data and mobile ad IDs (MAIDs) are the connective tissue for identity solutions. As we see those signals go away, there are fewer linkages to resolve identity and it’s leading to a rise in fragmented, duplicated, and shallow identity.
Recession fears
In addition to everything happening in AdTech, there are also fears of a possible recession. According to Forrester, 40% of Gen Z and 41% of Millennials believe fears of an upcoming recession are greatly exaggerated. On the other hand, only 24% of Gen X and 12% of Baby Boomers agree.4
Navigate uncertainty and marketing in a recession
With the current macroeconomic conditions, data deprecation, and fragmented consumption in mind, what should your strategy look like for marketing in a recession? Forrester recommends three strategies:
- People-led planning
- Test creative
- Optimize for marginal costs
People-led planning
Planning doesn’t have to be fragmented. Map offline and online media exposures to consumer decision journeys. Strategies like lifetime value (LTV) driven audience segmentation to correlate awareness at top of the funnel layered with demand generation exposures harvested later in the funnel. To do this, it’s crucial to work with providers that give you visibility into the audience buyer’s journey to awareness, intent, consideration, and purchase, all the way through to loyalty.5
Test creative
Make your creative work harder for you. Apply the same rigor with your creative that you applied to segmentation. Utilize multivariate testing to identify creative that is winning or losing. When you understand how each variable performs, you can scale the variables with creative optimization to have a material impact on performance.
Optimize for marginal costs
Optimize for marginal costs of acquisition, not just the average. Adjust for incrementality – what is the cost to acquire one more customer, rather than the average cost of acquisition.
Find the right marketing mix in a recession
With these changes in mind, how can you find the right marketing mix in a recession? We can show you the way.
You can create the right marketing mix with three key ingredients:
- Audiences
- Identity
- Activation
Let’s explore each ingredient to start you down the path toward marketing campaign success.
Audiences: Know your customer
The first ingredient to add to your marketing mix in a recession is your audience. Knowing your customer is key to targeting the right audiences successfully. Data-driven targeting can help you find your best audiences based on demographics, modeled lifestyles, and behaviors to improve marketing campaign performance.
Not sure where to start when it comes to developing your target audience strategy? We can help. We track digital usage of our data used by advertisers and identified the top four digital audiences that advertisers purchased over the last four years.
Four digital audiences to consider
Marketing strategies are only as strong as the data foundation they’re built on. The top four digital audiences that advertisers are purchasing from Experian include:
- Demographics
- Behavioral
- Modeled Lifestyles
- Custom Audiences
Demographics
Examples include age, gender, relationship status, living situation, life experience, and employment.
Behavioral
This audience allows marketers to identify households that are more likely to engage in certain activities or belong to certain groups.
Modeled Lifestyles
Experian’s Mosaic® USA segmentation. This is a household-based consumer lifestyle segmentation system that classifies all U.S. households and neighborhoods into 71 unique types and 19 overarching groups, providing a 360-degree view of consumers’ choices, preferences, and habits.
Custom Audiences
This is an audience blended from multiple sources or derived from first-party look-alike modeling.
Changes in digital audience strategies
Over the last four years, Modeled Lifestyles and Custom Audience purchases represented the smallest share of digital activation, while Behavioral and Demographic segments were more popular with advertisers.
When the U.S. rolled out the COVID-19 vaccine, consumers became more active. People were shopping in stores, returning to the gym, and taking trips that they had postponed during the height of the pandemic. Marketers turned to higher compositions of Demographic and Modeled Lifestyles to reach these audiences between April and December of 2021.
Sustained growth in Demographic audience activation could suggest a move back to tried and true audience strategies as signals continue to decline and amid evolving regulation. With economic uncertainty, marketers return to what they know. Traditional targeting methods like Demographics and Modeled Lifestyles are the baseline of many marketing strategies and we predict that we will continue to see marketers activating against these data sets.
Download our 2023 digital audience trends and predictions report to discover our full insights on how digital activation has changed and where we’re headed.
Identity: Understand the customer journey
Identity resolution is the next ingredient that you should add to your marketing mix in a recession. It should be a foundational element of every marketer’s strategy.
What is identity resolution? In the simplest terms, identity resolution is the process of matching different devices, IDs, and touchpoints back to a single person. Identity resolution expands marketers’ addressability and reach of their target audience and helps inform and measure accurate customer journeys.
Identity resolution challenges
Identity resolution faces two main challenges:
- Making the data actionable. Humans are complex. We have behaviors that change based on our current social groups and life events, we use dozens of internet-connected devices in a single day, and we exhibit distinct behaviors that happen online and in the physical world. This means marketers have mounds of data being collected from different channels based on that dynamic behavior of people, making it feel impossible to organize the data in a way that makes it feel actionable, know how it ties back to real humans, and ensure they’re doing it in a responsible and compliant way.
- Signal loss. Marketers continue to lose important signals that they’ve previously been able to rely on to inform their next move. Signals are being lost as our industry places more privacy regulations and restrictions on what can be tracked and as consumers themselves change behaviors to protect their privacy.
As consumer behaviors continue to change and signals disappear, identity resolution gets exponentially harder.
Expand addressability and reach with identity resolution
Data deprecation adversely affects identity solutions, but identity resolution should be a key ingredient in your marketing mix. Identity resolution ensures that consumers experience more relevant products, offers, and messaging – allowing you to reap the ROI benefits of hitting consumers at the perfect point in their journey.
Finding an identity resolution partner
When selecting an identity resolution partner, you should understand the data and processes that are implemented behind the scenes. It’s important to know:
- What makes up their consumer database?
- How fresh is their data?
- What identifiers can they match?
- How do they protect consumer privacy?
At Experian, we’re rooted in deterministic offline data which creates a stable foundation. We then layer in digital and behavioral touchpoints. We have decades of experience managing consumer data safely. We have insights on 250 million individuals, three billion devices, and one trillion device signals. Our databases evolve as quickly as the human behavior powering them does.
Our approach to identity resolution is open and agnostic. This means we can collect and ingest nearly all available offline and online identifiers. We can do this in all types of environments, including connected TV (CTV), mobile, and cookieless. We have two types of identity resolution:
- Offline
- Digital
This ensures we control how known and anonymous data points are connected for consumer privacy purposes.
Identity resolution in action
Our depth of data gives our clients access to see the whole human and gain the context around singular data points.
Let’s walk through an example of our identity resolution capabilities.
Challenge
Our TV media platform client needed to measure the effectiveness of an ad campaign they were running on behalf of a leading consumer electronics brand. The TV platform wanted to be able to accurately report on which consumers made a purchase after seeing the brand’s TV commercial on their platforms.
Solution
Using our digital identity resolution services, our client could capture online purchases made on the brand’s website and link them back to a consumer profile. In addition to online transactions, our client used our offline resolution services to resolve email addresses of consumers that purchased offline, using warranty registration details.
With online and offline purchase data now resolved back to an individual ID, we also performed identity resolution on viewers in their TV subscriber files that had also been exposed to the TV commercial. This allowed us to identify subscribers that had both seen the ad and purchased a product.
We provided our client with a packaged report that they could white-label and pass along to the brand.
Results
By providing this attribution reporting to the brand, the TV platform could validate the ROI spent on their platform. The brand was extremely satisfied with the results, and they transitioned the one-off TV commercial into an ongoing campaign and purchased quarterly measurement. This led to solid recurring revenue for the TV platform.
Activation: Experiment and measure the impact
The third and final ingredient to finding the right marketing mix in a recession is activation. Experimentation is the best way to determine which channels work best for your business and provide the most ROI.
Demand-side platforms (DSP), video platforms, and sell-side targeting are three important activation channels that you should consider experimenting with.
Demand-side platforms
We continue to see increased demand for environments where alternative identifiers are being transacted (like DSPs and video). Social channels are decreasing; this can be attributed to changes in privacy, security, and concerns around brand safety.
Amazon’s DSP is catching up with Google and Meta to become a top ad platform.
Video platforms
Digital video and other video channels like over-the-top (OTT) and CTV will continue to grow. Digital video will capture the most ad spend in 2023 (22.4% in 2023 vs 19.3% in 2022). Because of this, advertisers are placing bigger bets on the combination of addressable and CTV.
Sell-side targeting
Data sharing relationships will become strongest on the sell-side as we move toward consented first-party data. Ad dollars are shifting to channels that use the sell-side approach, like retail media and CTV.
Sell-side targeting enables brands to access large amounts of inventory across publishers and retailers. By getting closer to the ad inventory, advertisers can future-proof their strategies by having more access to better data signals. Direct relationships like these will be necessary as privacy regulations increase and signal loss continues.
We can help you find the right marketing mix in a recession
Now is the time to be opportunistic. Gaining share of voice during a downturn is cost-effective. Proactive marketing builds pent-up demand.
Delivering the right message in the right place at the right time means truly knowing your prospects and customers as individuals. At Experian, we bring you the highest-resolution picture of people, so you and your customers can connect with confidence.
You can turn prospects into customers with the right audience. By understanding your customers better, you can find more like them. Together we can power better results.
Find the right marketing mix
Check out our webinar, “Find the right marketing mix with rising consumer expectations.” Guest speaker, Nikhil Lai, Senior Analyst from Forrester Research, joined Experian experts Erin Haselkorn and Eden Wilbur. Watch the recording to learn:
- New data on the complexity and uncertainty facing marketers
- Consumer trends for 2023
- Recommendations on finding the right channel mix and the right consumers
Sources
- 2022 Retail Media Ad Sales Forecast, US. Forrester Research, Inc. 2022.
- Forrester Analytics Consumer Technographics® Technology, Media, and Telecom Topic Insights 1 Survey. Forrester Research, Inc. 2020.
- CMO Pulse Survey. Forrester Research, Inc. July 2021.
- Forrester’s Consumer Energy And Retail Online Survey. Forrester Research, Inc.
- People-Led Planning Solves Customer Problems to Drive Growth. Forrester Research, Inc. August 2, 2021.
Latest posts
Published in MediaPost With the explosion of smartphones and digital tablets and the steady rise of Internet-connected televisions, gaming consoles, and more, consumers are increasingly watching online video when and where they want. New research from Experian Marketing Services on cross-device video found that as of October 2013, 48% of all U.S. adults and 67% of those under the age of 35 watched online video during a typical week, up from 45% and 64%, respectively, just six months earlier. At the same time, the share of households considered “cord-cutters” — those with high speed Internet but no cable or satellite TV — is on the rise, and that has a real impact on marketers and on the medium of television, the recipient of the largest share of advertising dollars. While the growing trend in cord-cutting is understandably disturbing to cable and satellite companies and disruptive to the television advertising revenue model overall, the growth in online viewing creates opportunities for marketers. Online video viewers can be more easily targeted and served up advertising that is more relevant, responsive and measureable. Marketers can also be more confident that their online ad was actually seen given that viewers are typically unable to skip ads. And while CPMs for online video ads may generally be lower than those of TV, marketers can use that savings to negotiate costs based on clicks or transactions rather than impressions, giving them a better picture into audience interest and insights to inform their budget allocation. Expect “Cutting the cord” to continue Today, over 7.6 million U.S. homes or 6.5% of households are cord-cutters, up from 5.1 million in 2010 or 4.5% of households. One thing enabling consumers to cut the cord is the rise in Internet-connected TVs, which allows viewing of Internet video on demand without sacrificing screen size. In fact, a third of adults (34%) now have at least one TV in the home that is connected to the Internet either directly or through a separate device like an Apple TV or Roku, up from 25% in 2012. With the launch of devices like Google’s Chromecast and the Amazon Fire TV, those numbers are sure to rise even more in the months and years ahead. Cord-cutters like the bigger screen Our analysis found that the act of watching streaming or downloaded video on any device is connected to higher rates of cord-cutting but the act of watching on a television is the most highly correlated. In fact, adults who watch online video on a television are 3.2 times more likely than average to be cord-cutters. Those who watch video on their phone (the device identified in the analysis as that most commonly used for watching online video) are just 50% more likely to be cord-cutters. Millennials are more likely to be cord-cutters We found that households with an adult under the age of 35 are almost twice as likely to be cord-cutters. Throw a Netflix or Hulu account into the mix and the rate of cord-cutting among young adult households jumps to nearly one-in-four. Given these surprising stats, many Millennials may be cord-cutters without ever having “cut” a cord. And that’s an important trend to watch since it means a significant portion of this generation will never pay for TV. Millennials are also the most device-agnostic, with over a third saying they don’t mind watching video on a portable device even if it means a smaller screen. That’s more than double the rate of those ages 35 and older. This decentralized viewing can create headaches for marketers who need to start a relationship with Millennials during this stage of their lives when they’re most open to trying out new brands and have yet to settle down. On the plus side, marketers who do manage to reach this audience will find them much more open to advertising than average. In fact, Millennials are more than four times more likely to say that video ads that they view on their cell phone are useful. So while the challenge is big, so is the potential reward.
Published in AdExchanger. “Data-Driven Thinking" is written by members of the media community and contains fresh ideas on the digital revolution in media. Today’s column is written by Tom Manvydas, vice president of advertising strategy and solutions at Experian Marketing Services. The proliferation of connected electronics has spurred new interest in device-recognition technologies even though they have been in use since the 1990s. As we enter the “Internet of Things” era, device recognition will significantly impact the ad tech ecosystem. Many network advertising technologies are becoming obsolete as cookie blocking grows and the Internet becomes more mobile and device-centric. Device recognition will be yet another technology challenge for marketers but has the potential to overcome many key tracking, measurement and privacy issues with which data-driven marketers have struggled. By leveraging device recognition technologies, marketers can protect their investments in Web 2.0 ad tech, like multitouch attribution, and improve their overall digital marketing programs. Device Recognition Vs. Cookies Device recognition attempts to assign uniqueness to connected devices. By focusing on the device, you are able to “bridge” between browsers and apps, desktop to mobile and across OS platforms like iOS and Android. Device-recognition IDs function like desktop cookies for devices but with four important differences: 1. Coverage: Device-recognition methods are largely immune from cookie limitations. About half of mobile engagements on the Web do not involve cookies, while third-party blocking impacts up to 40% of desktop engagements. 2. Persistency: Device-recognition IDs can be more persistent and less fragmented than most desktop cookies. For example, Apple’s UDID or Android ID are permanent, and network node IDs like MAC addresses are near-permanent. Proxy IDs such as IDFA are persistent but can be updated by the device owner or ID provider. 3. Uniqueness: Devices are unique and cookies are fragmented. The digital media industry incurs substantial overhead cost and loss of efficiency when dealing with fragmented profiles and obsolete data caused by cookie churn. However, device-recognition methods are limited in their ability to recognize multiple profiles on shared devices. 4. Universality: Device-recognition technologies are universal and generally work across devices and networks. However, interoperability issues across device operating systems, such as iOS and Android, can limit the universal concept. There are many types of device-recognition technologies but two basic approaches to device recognition: deterministic and probabilistic, each with their pros and cons. Deterministic Approach: Accurate And Persistent But Complicated Deterministic device recognition primarily uses the collection of various IDs. While the mobile developer is familiar with the variety of IDs, it’s important that marketers become better-versed in this area. Examples include hardware IDs (including serial numbers), software-based device IDs (such as Apple’s UDID or the Android ID), digital data packet postal codes or proxy IDs (such as MAC addresses for WiFi or Bluetooth, IDFA for both iOS and Android and open-source IDs). Deterministic methods improve the accuracy of tracking, targeting and measurement over current cookie-based methods. They can improve the ability to more persistently manage consumer opt-outs. But the proliferation of device types limits the universality of deterministic device recognition. Without uniform standards across platforms, marketers need to account for multiple ID types. Also, deterministic device-recognition methods are not well developed for desktop marketing applications. The lack of interoperability across deterministic device IDs makes execution too complicated. Deterministic device IDs were meant for well-intentioned uses, such as tracking the carrier billing for a device. However, they present privacy and data rights challenges, leading to blocking or limited access by companies that control IDs. Probabilistic Device Recognition: A ‘Goldilocks’ Solution Probabilistic device recognition may be the ideal solution for a connected world that does not rely on cookies nor wants to use overly intrusive deterministic device recognition. Probabilistic device recognition is not a replacement for deterministic IDs. Instead, it complements their function and provides coverage when they are not available. The probabilistic approach is based on a statistical probability of uniqueness for any single device profile. This approach creates a unique profile based on a large number of common parameters, such as screen resolution, device type and operating system. This process can uniquely identify a device profile with 60% to 90% accuracy, compared to 20% to 85% accuracy for cookie-based identification methods. Probabilistic IDs are more persistent than cookies with better coverage, but less persistent than deterministic device IDs. The natural evolution of the device takes place over time and prevents persistent identification. Probabilistic device recognition can be universal and is not impacted by interoperability issues across platforms — the technology used to generate a probabilistic ID on one network can be the same technology on another network. Unlike some deterministic device recognition approaches, there is no device fingerprinting. Probabilistic device recognition accurately identifies profiles in aggregate, rather than a single device. That’s the inherent beauty of probabilistic device recognition: It can generate more accurate targeting results than cookie-based methods without explicitly identifying single devices. This is more than good enough for most marketers and significantly better than what’s available today. Another benefit is the absence of any residue on the device — no cookie files, flash files or hidden markers. Probabilistic methods can work on devices that block third-party cookies or connect to the Web without using any cookies. For example, you might have a hard-to-reach but valuable audience segment. Probabilistic device recognition could effectively increase your reach on this segment by 40% to 50% and increase the overall targeting accuracy by two times. Let’s say the actual population for this segment is 100,000 members. The typical cookie-based approach might reach 28,000 members but the typical probabilistic device-recognition approach could reach 65,000 members. A Decline In Hardware Entropy If you take a close look at the emitted data from today’s devices, it is not easy to analyze it for device identification. That’s because the data footprint of one device looks a lot like another. Device recognition augmentation methods can address this, such as device usage profiles, geo location clustering, cross-device/screen analytics or ID linkage for first-party data owners. In the short term, device-recognition technologies, particularly probabilistic methods, can greatly improve today’s digital marketing programs. Marketers should become fluent in their use cases and benefits. If 2013 was the year of mobile, I think we’ll see a surge in marketing applications based on device-recognition technologies in 2014. Follow Experian Marketing Services (@ExperianMkt) and AdExchanger (@adexchanger) on Twitter.
According to Experian Marketing Services’ 2014 Digital Marketer: Benchmark and Trend Report, social media Websites are playing an increasingly important role in driving traffic to other Websites, including retail sites and even other social networking sites, at the expense of search engines and portal pages. For instance, as of March 2014, social media sites account for 7.72 percent of all traffic to retail Websites, up from 6.59 percent in March 2013. Further, Pinterest, more than Facebook or YouTube, is supplying the greatest percentage of downstream traffic to retail sites. According to the Digital Marketer Report, more retailers are directing their customers to social media within their email campaigns. In fact, 96 percent of marketers now promote social media in their emails, and it shows. In 2013, for instance, email Websites generated 18 percent more clicks to social networking pages than the year prior. Social drives more traffic to other social Websites Social media Websites are driving more and more traffic to other social sites. In 2013, 15.1 percent of clicks to social networking and forum sites came from other social networking sites, up from a 12.5 percent click share reported in 2012. Despite driving the greatest share of traffic to social networking sites with 39.1 percent of clicks, search engines’ share of upstream traffic to social declined a relative 13 percent year-over-year. Among the other top referring industries to social, only the portal front pages industry — which includes sites like Yahoo!, MSN and AOL and is closely affiliated with search engines — showed a drop in upstream click share providing further evidence that increasingly all (or most) roads lead to social. To learn more about key trends in social media traffic, including downstream traffic from social sites and the share of consumers accessing social media across multiple channels, download the free 2014 Digital Marketer: Benchmark and Trend Report.