In our Ask the Expert Series, we interview leaders from our partner organizations who are helping lead their brands to new heights in AdTech. Today’s interview is with Rachel Herbstman, VP of Data Innovation, and Anastasia Dukes-Asuen, Senior Director of Advanced TV Data & Insights at Ampersand.
Could you introduce us to Ampersand and discuss your approach to TV advertising?
Ampersand, a joint venture between Comcast, Charter, and Cox, is a media sales organization that offers a unified footprint, unlocking unparalleled scale and unique data/insights for local and national advertisers. Ampersand gives advertisers true audience first planning, scale in execution, and advanced measurement of their TV investments, representing 117 million multiscreen households and over 75% of addressable households in the U.S. (64 million households). We help clients reach their unique target audience and deliver their stories – anytime, anywhere, and on whatever device.
How does adding streaming to a linear campaign, or vice versa, enhance overall campaign performance for marketers?
Herbstman: Marketers have recognized that multiscreen media strategies are the strongest as viewership continues to fragment. Unique audiences exist in traditional TV and streaming, and failure to include either media channel will reduce the total reach opportunity. These channels have proven to validate unduplicated audiences.
In our local business, adding streaming to a historically traditional linear-only media strategy increased campaign reach by 33%. Conversely, adding linear TV to a historically streaming-only media strategy increased reach by 209%. These metrics are validated by matching media exposures to an authenticated households subscriber ID and represent mass opportunities to reach new audiences with a multiscreen media strategy.
When considering reallocating media investments, how does Ampersand help clients determine the most effective channels for specific campaigns?
Herbstman: For a brand that historically invested in traditional TV, either national or local broadcast, we can provide insights to analyze the performance of any media campaign. The insights can include high-level metrics like reach and frequency and more granular metrics like unique reach per network. By seeing both the high-level results and more detailed granularity, we can provide optimization recommendations for funding other activation opportunities.
Our database of past campaigns consistently demonstrates that gaining new eyeballs with a national TV campaign usually plateaus after a few weeks. In other words, if most of your intended audience is reached after about three or four weeks of national television, reaching any new viewers can be exponentially more expensive.
We’ve built an Addressable Simulator tool for national advertisers that shows the potential impact of shifting a portion of the national media weight, specifically from the latter part of a flight, into addressable TV. Using our licensed Experian data set, we can measure any standard age/gender target or any advanced target to understand the complementary impact that addressable audience has on national media. This tool has dynamic inputs of CPMs and incidence rates, flight lengths, and budgets to simulate different scenarios and give marketers some intelligence on what holistic reach against that Experian segment they could expect with one given budget using brand-safe, traditional, and streaming inventory with an addressable activation.
Additionally, we’ve developed an interactive eCPM calculator that helps national advertisers assess the cost efficiency of adding addressable TV to their traditional campaigns. By dynamically inputting CPMs, marketers can evaluate tradeoffs between media types for upcoming campaigns.
Are there audience demographics that benefit from these combined media strategies, and what indicators or data points guide your recommendations to add cable to a local broadcast campaign versus other reallocations?
Herbstman: By including cable or streaming in a local effort, a client can use a data-driven approach to find more intended viewers in other premium content. Utilizing the vast library of Experian audience segments paired with our robust sample of 64 million data-enabled homes enables Ampersand to provide insights into the most valuable networks and dayparts that the intended viewer will likely watch on either platform.
With identity and viewing insights at scale, we can understand how consumers watch TV, even for inventory we have yet to sell. Our goal is to help marketers understand what’s happening as a result of their investments at a holistic level.
We can analyze a campaign running across hundreds of designated market areas to quickly and simply understand the holistic delivery of their broadcast and cable weight by pulling back set-top-box exposures on broadcast and Ampersand-purchased cable on our measurable footprint. Then, we can determine the share of measurable reach that each portion’s media weight contributes to.
We recommend optimizing towards a more balanced approach, where the reach levels for broadcast and cable mirror each other, creating a more effective market media mix.
Once we confirm cable’s potential in a market, we analyze network and daypart metrics to adjust key areas to optimize the campaign. We invite marketers to use these insights to measure their local or national TV campaign performance and garner unique perspectives to re-balance investments to drive reach and optimal frequencies.
Are there common missteps to avoid?
Dukes-Asuen: Ampersand’s decades of experience with media and data insights have allowed us to create an extensive database complete with targeting and measurement benchmarks. We use this database to curate best practices for brands and help set them up for success, keeping their goals and objectives for reach and frequency in mind.
Some clients spread their investment levels too thin, whether through short flight windows, low weekly frequencies, or targeting overly niche audiences that don’t fully support KPI goals.
One way to avoid these missteps is to set up a test-and-learn plan to validate a hypothesis and refine media strategies, ensuring campaigns are structured to garner meaningful insights. Ampersand can help ensure the test itself is constructed and supported to yield statistically relevant results, and the learnings can then be applied to the next campaign.
How does Experian’s data enhance your campaigns at Ampersand?
Dukes-Asuen: Within our Experian license, we can map the Experian Consumer View databases against our multichannel video programming distributors subscriber base in a privacy-compliant way to plan and activate them seamlessly. Experian has a rich set of audience targets and segmentation that we utilize to identify households that can be used for audience-based media execution with Ampersand. By defining the right audience—whether consumers are likely to purchase a product, exhibit certain behaviors, or demonstrate specific values—we enhance campaign performance and improve media spending efficiency for our advertisers.
Additionally, how do you believe AI and other new technologies will impact your media buying approaches in the future, and how might these innovations improve campaign effectiveness and provide value to your clients?
Herbstman: We have a strong use case on the measurement and analytics end. Using AI, we can aggregate a massive amount of historical data—viewership and exposure data. AI helps us understand overarching market trends and media performance to analyze campaign results and inform future campaign optimizations. The value of AI is in its role as an additional technology layer, enriching our insights portfolio and providing faster intelligence that enhances campaign effectiveness and delivers greater value to our clients.
Can you share an example of how precise audience targeting and segmentation, powered by Experian, have led to significantly better media spend reallocations and campaign performance for marketers?
One great example is how a national cruise brand dramatically improved its media spend and campaign performance by utilizing precise audience targeting and segmentation through Experian. By combining Ampersand’s addressable TV with Experian’s data-driven insights, they achieved a 14% incremental reach, a 3.1x higher frequency, and a 24% lower effective CPM. This strategic approach allowed them to reallocate their media spending more effectively, ensuring every impression reached their custom target audience.
Thanks for the interview.
For those interested in learning more about Ampersand, reach out for a personalized consultation.
Latest posts
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.
Mother’s Day may not exactly be right around the corner, but the time to send your Mother’s Day emails sure is! Based on our analysis of 186 brands that sent Mother’s Day mailings in 2013, 75 percent of email volume and 80 percent of email-generated revenue occurred between May 1st and Mother’s Day (May 12, 2013). The highest revenue-producing days were five days before the holiday (Wednesday, May 8, 2013) and Mother’s Day itself. This year, the sentimental holiday falls one day sooner than last year (May 11), but you still have more than enough time consider these quick tips for easy wins while planning and executing your campaigns. Tip 1: Give them what they’re searching for Last year, online searches five weeks before Mother’s Day were dominated by searches for the date of the holiday. As such, we recommend including the date of Mother’s Day in your email subject lines, particularly those early in the season, when customers are searching online for, and opening emails with, that information. Tip 2: Set the tone early with your subject lines A sample of early season subject lines that outperformed the overall unique open rate included: Remember Mom on Mother’s Day, May 12 Get a head start on Mother’s Day (plus a gift for you) Just arrived: Mother’s Day Gift Sets To Mother, With Love Tip 3: When it comes to timing, it’s the thought that counts Think through the timing of your emails depending on order delivery deadlines. On May 8th of last year, the largest revenue producers for email were orders for flowers and gifts placed in time to be delivered by Mother’s Day. Email subject lines on May 8th included reminders of the delivery deadlines: Last Chance: Free Shipping/No Service Charge for Mother’s Day! ENDS TODAY: Enjoy Complimentary Second Day Delivery in Time for Mother’s Day Tip 4: Let them treat themselves On Mother’s Day, the top email revenue generators were “self-gifting” (treat yourself on Mother’s Day only), Mother’s Day online sales and free shipping, as well as e-gift cards: Free Shipping Today Only! Happy Mother’s Day You deserve a treat yourself! HAPPY MOTHER’S DAY! Treat yourself to 30% off today only Last Chance: eGift Cards in Time for Mother’s Day Other email performance highlights: Note: All email performance highlights are based on comparisons to Mother’s Day mailings without the highlighted feature from matched brands. To all those in the midst of Mother’s Day campaign planning, good luck and happy sending!