Pinpointing Campaign Attribution Through Multiple Touchpoints: A View into MTA for CPG Brands

Transcription

1 Pinpointing Campaign Attribution Through Multiple Touchpoints: A View into MTA for CPG Brands JULY 2018

2 Executive Summary: Multi-Touch Attribution for CPG Where We Stand The percentage of budget spent on marketing analytics is expected to grow from 5.8 percent to 17.3 percent within the next three years, according to the 2018 CMO Survey. That s an impressive projected growth of 198 percent. Clearly, marketers value consumer data models that can give them keen insight into the consumer journey online and offline more than ever. Certainly, the explosive growth of digital advertising leaves a key question unanswered: How do we accurately attribute advertising and marketing spend? Today, a little over half of all U.S. companies use some form of multi-channel attribution 1. These companies understand that having a complete view of the consumer journey that may crisscross between offline and online touchpoints offers their marketers unprecedented insight into purchasing decisions on an immediate basis. Still, only 8 percent of client-side marketers worldwide have tied together customer data from multiple channels, technologies and databases 1. Those 8 percent of marketers understand that although there s no perfect solution today there must be an internal consensus, a focus on the value of the customer and ways to measure success via real business drivers (not channel-specific KPIs). In consumer goods, it is estimated that up to 95 percent of purchases are made offline, making it very tough to trace back and assign proper credit to different channels. Still, a growing number of CPG products are being purchased online, a trend that is sure to continue and potentially accelerate as services like Amazon and other similar online retailers continue to create value and convenience for the consumer. Given that the price point for many CPG products is low compared to other types of consumer purchases, multitouch attribution (MTA) in its current state is often not viewed as a cost-effective solution for CPG marketers. It s also true that MTA is in its infancy in the CPG domain. There is no solution that can merge online and offline touchpoints into one cohesive, rapid and actionable MTA model. However, through the convergence of advanced data, advertising technology and media, CPG marketers are able to tap into a hybrid of MTA and cross-channel measurement to gain actionable campaign insights, even for lower-price-point, high-frequency consumer purchases. EXHIBIT 1 Shopper marketing and digital advertising are growing rapidly, but trade promotion still accounts for over 40% of marketing spending. Manufacturer Marketing Spending by Type 49.8% 43.4% % 10.5% 7.1% 19.9% 25.4% 13.3% 6.0% 12.9% Consumer Promotion Trade Promotion Digital Traditional Advertising Shopper Marketing Credit: Cadet Consulting Group ¹ Source: emarketer, Marketing Attribution 2017: Five Best Practices 1

3 The Flavors of Attribution Models As we explore the value of MTA in the CPG universe, it s helpful to gain a deeper understanding of the most commonly used attribution models by marketing researchers. Marketing Mix (MMM) Primarily Offline The MMM attribution model analyzes aggregated historical data, most typically from offline media sources like TV, radio and print. Organizational-level metrics that are used for strategic planning, spending budgets and analyzing performance are usually delivered with a marketing mix model. A few facts about MMM: The MMM model takes a top-down, macro-level approach. It offers the marketer a more high-level view for tactical insights. The scope of analysis is broad and includes both internal and external factors. Factors may include anything from marketing, trade and pricing data to weather and even news events. The analysis is usually performed once or twice a year. EXHIBIT 2 Cross-tactic marketing mix measurement will decompose brand sales and quantify synergies. Sales and Brand Metrics Decomposition of Sales Weekly Sales 70,000 60,000 50,000 40,000 30,000 20,000 10, /6/17 10/20/17 11/3/17 11/17/17 12/1/17 12/15/17 12/29/17 1/12/18 1/26/18 2/9/18 2/23/18 Trade 9.0% Media 13.1% Synergy 1.0% Marketing Support 35,000 30,000 25,000 20,000 15,000 10,000 5, /6/17 10/20/17 11/3/17 11/17/17 12/1/17 12/15/17 12/29/17 1/12/18 1/26/18 2/9/18 2/23/18 Digital Display Online Video Print TV Paid Search Marketing Tactics Contribution TV 9.5% Dig. Display 0.8% Online Video 2.1% Print 0.5% Paid Search 0.5% Core 76.9% 2

4 Cross-Channel Lift (CCL) Offline and Online The Cross-Channel Lift model bridges the gap between a 30,000-foot view and granular tactical recommendations. It can look not only at the digital touchpoints but also at exposure from owned media programs (CRM) as well as in-store and TV. It can understand the synergistic effects at a granular level across target groups, creative, placement and frequency. A few facts about CCL: Multi-Touch Attribution (MTA) Primarily Online The MTA model takes a bottom-up, granular, usercentric approach. The focus is on the consumer s digital journey, looking at the path to conversion across multiple touchpoints and over a time period. MTA measures household-level or individual lift of marketing levers or a combination. Marketers can read the impact on clickthroughs and other digital engagement behavior lift, helping to provide greater focus on maximizing marketing spend return. Offers the ability to understand the marketing impact of single channels and the synergistic effects of multiple channels. It can identify and parse out both offline and online efforts. Across all campaigns, combining digital media with in-store merchandising support amplifies the message and increases the overall return on investment. Allows for the combination at an individual household level to not only understand the digital path but also bring together other elements like TV, in-store and owned-media programs. A few facts about MTA: Offers marketers more tactical campaign recommendations. Leverages individual, user-level data across addressable channels like direct mail, online display and paid search. Calculates and assigns fractional credit to the marketing touchpoints along the consumer journey that influenced a desired business outcome. Helps marketers gain a deep understanding of optimal channel allocations to inform media strategies. By understanding those households exposed across channels and screens, the ability to understand frequency in totality is increased. Offers the ability to help marketers better understand and react to what s happening daily, but also across campaigns over time. Helps marketers gain insights on how, when and where consumers are influenced across both devices and channels. 3

5 CPG Requirements for MTA In the CPG industry, there continues to be growing interest in attribution models, particularly MTA, because it holds the promise to combine the touchpoints longitudinally, giving marketers more real-time and long-term optimization potential. More CPG marketers are considering attribution models, especially with an increasing number of their products being purchased online. Also, until recently, most sales data in CPG was based on panels modeled to reflect census data. Only recently have companies been able to get householdbased sales data to start to measure the personalized channels insights that hold significant value to CPG marketers. EXHIBIT 3 Cross-Channel Lift shows how each granular tactic drives sales lift and how to optimize across each variable. Who? Target Demos, purchase behavior, etc. However, because of the nature of the CPG marketplace, marketers in this industry have unique challenges and requirements that impact their decision to use MTA as a viable and cost-effective tool. Marketers in the CPG industry will value an MTA solution that: Where? Channel TV, digital, mobile, print, radio, network, publisher, etc. Weights both online and offline campaign touchpoints effectively in a tunable, bespoke fashion versus a one-size-fits-all way of attributing value. Meets or exceeds ROI thresholds to justify the investment, especially for lower-priced (though frequently purchased) CPG products. Offers accurate and granular information to apprise the brand on direction and action. How often? Frequency # exposures per HH per week Ad Type Video, static, dynamic, etc. Enables in-flight campaign adjustments for near-real-time optimization. Provides deep insights on how tactics are driving sales lift and are optimized across each other, including actionable data on target, channel, frequency, ad type, creative and ad size. Combines household-level sales data alongside store or trade-area sales data to ensure a balanced view, including all channels from broadcast to personalized with the best accuracy. With what? Creative Call to action, promotion, etc. Ad Size Duration, length and width, etc. 4

6 What Attribution Model Should You Use? Today s marketers face the significant challenge of measuring the impact of online impressions, offline activity and purchases. Data analytics and attribution models, in theory, are supposed to help traverse the consumer journey through strategy insights, as well as navigate the spiderweb of touchpoints at a granular level in and out of offline and online activity to give credit where credit is due. Each solution discussed above offers some distinct advantages, yet it is still paramount to consider the desired outcome and the tactics employed to ensure the best solution is being utilized. For CPG brands who have distinct challenges like the current percentage of business conducted offline and low price points, a hybrid approach that offers key benefits from all these attribution models is a better choice. A unique and approachable solve is to address a measurement solution that offers an attribution model that resembles MTA with features of MMM combined with a more granular Cross-Channel Lift solution. This unique combination allows CPG marketers to: Get visibility into overall performance across media activations via marketing mix (big-picture performance metrics by platform), while Getting more granular and tactical reads across all media tactics that provide Performance at the campaign level in as little as three weeks (and weekly after that) for optimization. Modify the Lift methodology to evaluate a broader dataset looking across multiple campaigns over time, leveraging a key advantage of MTA. 5

7 The CPG Reality and Potential for Today s MTA Cross-Channel Model MTA has limitations within CPG and is not yet ready for consideration as the gold standard. It will be a challenge to fully develop MTA within CPG since 95 percent of all sales occur offline. This offline dominance makes it very challenging to assign proper credit to individual touchpoints, let alone pinpoint synergies or any campaign optimization tactics with confidence. When we look realistically at where we are today, several factors are important for CPG marketers to ponder when assessing attribution models: By far the most important consideration: quality and freshness of offline purchase data leveraged by the solution. Data at scale provides more accurate results and enhanced granularity, increasing the speed with which marketers can act. There are several players in the space that can do some combination of MMM, MTA and CCL with different levels of data access and measurement methodologies. Be aware of the partner s technology platform, since visualization of data and insights will be particularly important due to the costs associated with each measurement option. Opportunities Presented by IRI s Cross-Channel Attribution Products Today s CPG marketers do have access to current and proven solutions that work similarly to full MTA solutions. IRI s sophisticated and accurate Cross-Channel Lift solution gets you 90 percent there today, at significantly less time and cost investment, and with more offline sales data than most MTA solutions have available. IRI Marketing Mix and IRI Lift are proven products that are available now and can provide metrics and insights to help inform, both on a holistic and tactical campaign level. Additional competencies and capabilities for consideration: IRI is a leader of unified measurement based on The Forrester Wave : Marketing Measurement and Optimization Solutions 2018 results. IRI has the largest loyalty card dataset, providing linkage to CPG sales for 85 percent of U.S. households. Our partnership ecosystem allows for assessment of digital, TV, social, in-store and CRM program exposure. Understanding which KPIs are significant and appropriate for your brand is key because the difficulty of calculating the impact of fractional weights makes ROAS optimization challenging with MTA solutions. Our solid, granular, best-in-class analytic models use a vast amount of data, such as FSP, pricing, assortment, marketing mix and attribution, all of which are fully embedded into the platform and applications. IRI is in a unique position to meet these challenges, since our offline sales data is composed of 350 million loyalty cards, which translates into 107 million individual households, allowing for attribution of exposures to offline sales. This linkage allows for measurement at a granular level and is further fueling development of an MTA solution with cross-channel features that will be a solve for CPG brands. Leading technology platform with IRI Liquid Data and IRI Lift: By combining Liquid Data the industry-leading, cloud-based, real-time big data management analytics platform and Lift the revolutionary application that ties media exposure to sales for unprecedented ad impact measurement and optimization brands can achieve an unprecedented level of marketing precision that will drive sales growth. 6

8 Our solution is fast (three weeks from campaign start, plus weekly updates) and less expensive, especially for consumer products. Overall, we have found that our clients improve their ROAS by up to 80 percent by taking advantage of in-flight optimization opportunities. Our solution looks at each tactic holistically and allocates or optimizes, which integrates a vital nuance missing from MTA: fractional credits. How It Works The lens providing visibility into CPG attribution today getting us 90 percent there is the IRI Cross- Channel Lift solution. IRI Cross-Channel Lift is primarily designed to provide advertisers with a means to make in-flight optimization decisions based on sales impact within weeks of a campaign launch. Through IRI Cross-Channel Lift, advertisers have the opportunity to drive up sales, penetration, dollars per trip, number of trips and ROAS by focusing remaining media dollars behind the campaign s areas of strength across several dimensions. These might include platform, creative, target group, ad type and more. Learnings can also be applied to future campaigns. IRI Cross-Channel Lift is: Accurate: highly accurate and precise results, driven by our best-in-class methodology and data assets. Combining exposure data from both television and digital sources provides marketers with a single crosschannel total campaign dataset. Granular: deeper, more precise and granular views, enabled by the number of households captured in our datasets. FSP: Our database of more than 350 million FSP cards provides keen perspective at test and control household behaviors across four key metrics before, during and after the campaign period. National Consumer Panel: Comparing pre- and postperiod test and control data to the NCP (110,000 households) ensures that FSP data is representative. Point of Sale: Store data is used to weight the Lift results for each channel, and to model to control for variables driving sales in stores that aren t associated with the media. Third Party: Experian/LiveRamp data adds non-pii common IDs, publisher cookies and mobile IDs; comscore/alphonso digital and TV exposure data. Fast: quicker measurement results and in-flight optimization opportunities, supported by our cutting-edge technology platform. EXHIBIT 4 Hold media accountable with Lift, an analytical powerhouse for in-flight measurement and optimization. How does it help? Reads within weeks identify opportunities for improved efficiency & effectiveness. +80% ROAS Audience households are classified based on their exposure to one or both channels, and are matched to a control that has not been exposed to either channel. This combined view allows for the calculation of lift by each individual channel, as well as measurement of the impact of multi-channel exposures and their potential synergies. ROAS without optimization ROAS with Lift optimization Improvement ranges from 30% to 80% 7

9 Case Study Food Brand Closes 20-Point Performance Gap with Mid-Campaign Optimization A CPG food brand recently focused on optimizing a 16-week TV and digital advertising campaign leveraging IRI Cross-Channel Lift, with the goal of maximizing synergies across the two channels to increase penetration and boost return on a $12 million advertising campaign investment. Through this optimization effort, the client was able to close a significant performance gap versus other publishers and finish the campaign on parity. Meanwhile, synergies with other channels yield 2 to 6 times the lift of individual channels. $ Uplift by Channel $2.39 $2.69 $3.26 $2.99 $3.31 Multi-Channel Synergy $2.69 $2.60 $3.18 $2.93 $6.90 $7.35 $7.98 Tapping into multiple data sources created sufficient sample size to create a high level of accuracy, averaging 98.4 percent sensitivity. Television and display drove penetration, while mobile increased purchase occasions. EXHIBIT 5 TV, display drove penetration while mobile increased purchase occasions. TV ONLY +4.4% penetration uplift among households exposed to TV vs. unexposed control ONLINE DISPLAY +1.5% penetration uplift among households exposed to online display vs. unexposed control MOBILE ONLY +3.0% purchase occasion uplift among households exposed to mobile vs. unexposed control TV Online Display Shifting impressions within programmatic to higher share of animated ads mid-campaign closed a 20 percent performance gap by the end of the campaign and gave the client the insights needed to direct the agency to narrow audience focus to top-performing audiences with mutual exclusivity. Switcher High Propensity Buyer Loyalist Competitive Buyer Demographic Income Demographic Gender Geographic High Propensity to Buy Competitive Income Demographic Demographic Age Demographic Family Size Switcher High Propensity Buyer Loyalist Competitive Buyer Demographic Income Demographic Gender Geographic High Propensity to Buy Competitive Income Demographic Demographic Age Demographic Family Size Mobile TV + Online Display TV + Mobile % Lift by Audience Online Display + Mobile TV + Online Display + Mobile # Impressions by Audience 0 500,000 1,000,000 1,500,000 2,000,000 Analysis Time Period: Campaign End + 4 week lag (20 weeks) 8

10 Conclusion Marketers are coming under increasing pressure to justify marketing spend. Attribution modeling has become a high priority not just in demonstrating the value of ad budgets, but in giving credit where credit is due. Unfortunately, today s attribution models are not fully capable of traversing the spiderweb of an online and offline journey that ultimately results in a purchase. Traditionally, MTA attribution models have also often been expensive, making their use with lower-priced CPG products less worthwhile. However, it is possible today to use a currently available cross-channel solution with multi-touch attribution features that offers access to a deep well of offline household-level data and online touchpoints at an unprecedented low cost. As e-commerce penetration continues and addressability across the major media channels improves, MTA is likely to rise to the surface as a gold-standard methodology. Until that happens, the hybrid cross-channel multi-touch attribution model is an ideal approach. 9

11 ABOUT THE AUTHORS Jennifer Pelino, senior vice president of omnichannel media, IRI Media Center of Excellence in the Chicago headquarters of IRI. You may contact her via at Vijoy Gopalakrishnan, senior vice president of product development, IRI Media Center of Excellence in the Chicago headquarters of IRI. You may contact him by at About IRI IRI is a leading provider of big data, predictive analytics and forward-looking insights that help CPG, OTC health care organizations, retailers and media companies to grow their businesses. With the largest repository of purchase, media, social, causal and loyalty data, all integrated on an on-demand, cloud-based technology platform, IRI helps to guide its more than 5,000 clients around the world in their quests to remain relentlessly relevant, capture market share, connect with consumers and deliver market-leading growth. A confluence of major external events a revolution in consumer buying, big data coming into its own, advanced analytics and automated consumer activation is leading to a seismic shift in drivers of success in all industries. Ensure your business can leverage data at Corporate Headquarters: 150 North Clinton St., Chicago, IL 60661, USA, (312) Copyright 2018 Information Resources, Inc. (IRI). All rights reserved. IRI, the IRI logo, and the names of IRI products and services referenced herein are either trademarks or registered trademarks of IRI. All other trademarks are the property of their respective owners.