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Full Funnel Marketing Case Study

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Full Funnel Marketing Case Study

  1. 1. A CASE FOR INVESTING IN FULL FUNNEL DIGITAL MARKETING As the industry debates the merits of Upper Funnel tactics, their true value can be found by looking at their influence across all KPIs. July 2014
  2. 2. With today’s consumers having so much control over the messages delivered to them, a greater understanding of the consumer journey is crucial for marketing success. Brands must be able to reach their customers in ways that are relevant, meaningful and add value to their day. Key to doing so is creating effective media strategies that successfully engage consumers across the entire Marketing Funnel. In the context of the Digital Media Marketing Funnel, increasing brand awareness is the goal of Upper Funnel programs. For the context of this case study, we are defining Upper Funnel campaigns as those with the objective of driving the right audience to the brand’s site. Tactics that do so include Filtering and Prospecting. Filtering uses demographic data, such as time-of-day, day-of-week, inventory source, geography, browser type or ISP, to target audiences, whereas Prospecting uses licensed third-party data to target a specific audience. Lower Funnel programs seek to convert leads into opportunities. This is done through a tactic called Remarketing. Remarketing uses first-party data to reach consumers who have previously engaged with a brand. Clients often judge an Upper Funnel tactic by the same Key Performance Indicators (KPIs) as Lower Funnel tactics. At Audience On Demand® (AOD), we believe that judgment is flawed, as each tactic along the funnel has its own objective and should be judged accordingly. To demonstrate this, AOD proactively researched and analyzed the effect of of Upper Funnel tactics on Lower Funnel activity on a campaign-by-campaign basis. While this same analysis technique can be applied more broadly than to just the display channel, in this case, AOD focused on programmatic display. Leveraging VivaKi’s big data solution, SkySkraper, AOD was able to access log- level data and custom reporting from multiple DSPs for campaigns across various verticals, as well as use external research findings. + As part of AOD’s regular practice, numerous campaigns across verticals and KPIs were analyzed, and four were highlighted for this study. + Conversion rates, click-thru-rates (CTR) and Unique User (UU) volume were used to compare users touched by Upper Funnel tactics and driven into Remarketing (REM), versus those organically reached by REM. WHAT We Wanted to Achieve. HOW We Did It.
  3. 3. The results of AOD’s research and analysis showed that Upper Funnel tactics had a strong positive influence on Lower Funnel strategies. Campaigns that used a Full Funnel approach yielded better results than those that used just the REM strategy alone, regardless of KPI. In short, campaigns that used a Full Funnel approach drove more conversions. Here’s how: RESULTS Users viewing Upper Funnel ads clicked through to tagged landing pages, feeding them into the REM pool. + Higher click volumes on Upper Funnel ads resulted in more users being added into the REM pool. + More users in the REM pool gave REM campaigns higher reach, leading to greater opportunity for improved performance. + In one example, more than 10 percent of users who were shown an Upper Funnel ad were driven to the REM pool. Grow REM pool More clicks1 10%+ of Prospecting UU’s were driven into the REM pool, adding over 3,500 people that can now be targeted by Lower Funnel campaigns. In another example, over 4% of UU’s who were served Prospecting ads clicked and were subsequently served REM ads as well. 3,659 35,916 UU’s in Prospecting UU’s driven to Remarketing 19,362 479,622 UU’s in Prospecting UU’s reached by Remarketing Client A Client B
  4. 4. REM-only UU’s Conversion rate 0.00375% REM UU’s Upper Funnel UU’s Conversion rate 0.0613% Purchase conversion rate was 64% higher when users were touched by both Upper and Lower Funnel targeted impressions, rather than just REM alone. Delta of 64% Users who clicked on Upper Funnel ads and were subsequently served REM ads were more likely to convert. + Those who had previously interacted with an Upper Funnel ad comprised a more relevant and tailored audience. + Remarketing to potential converters kept a product/incentive top-of-mind and may have tipped an already susceptible user to convert. + Conversions by users driven through the funnel accounted for approximately 20 percent of total REM conversions. Add more qualified users Higher conversion rate2 Client C
  5. 5. Running Upper and Lower Funnel tactics in tandem increased conversion volume via incremental conversions. + Upper Funnel tactics captured new users, which continuously refreshed the REM pool. + Once these users converted, they were considered incremental, as they may not have been remarketed to otherwise. Garner incremental conversions Higher conversion volume3 Unique Users UU’s reached by Remarketing UU’s then converting in REM 3,861 Total REM Conversions 3rd Party Data Filtering Private Deals 14,387,644 46,798 507 (13%) 240,056,56 96,292 956 (25%) 111,495,841 148,173 1,196 (31% of Total REM Conversions) Conversion rate was 80% to 110% higher when UU’s were touched by Full Funnel tactics than when touch by only Remarketing. Client D
  6. 6. CPC: An Alternative KPI Sometimes, a lack of resources (log-level data, storage space, advanced analytics tools, etc.) can limit the ability to track a user through the funnel. While Upper Funnel tactics cannot always compete with REM tactics from a CPA perspective, they are still valuable for growing the REM pool. In these instances, Cost Per Clicks (CPC) can serve as an alternative KPI for Upper Funnel tactics, measuring the efficiency of driving users to the REM pool. Here’s how it works: CLICKS A click on an Upper Funnel ad will drive to a REM tagged page. COOKIED USER A user will be cookied when they arrive on the landing page, bucketing them into the REM pool. RATIOS Lower CPC’s mean that users are being driven to the remarketing pool more efficiently. CPC Looking at CPC in the Upper Funnel portion of the campaign acts as a proxy for the cost of adding users to the REM pool.
  7. 7. About AOD Analytics Priyanka Naik came to AOD with a background in management consulting. In her role as analyst, she consistently applies her creative strategic and analytical insight to all of her clients, which fall across a wide range of industry verticals. Priyanka has contributed to the AOD Analytics Team by pioneering programs such as “Analyst of the Month” and a training on “How to Present Data.” Outside of AOD, Priyanka’s passion is cooking, and she shares recipes and reviews on her personal blog, chefpriyanka.com. Priyanka graduated with a Bachelor of Arts in Economics from Boston University. Priyanka Naik Tim Slater Nina Van Brunt Tim Slater joined AOD as an Ad Ops Coordinator after graduating from Grand Valley State University with a BBA in Marketing. After working on the Mediavest business, he segued into working as an analyst on Starcom and other assorted AOD business. During 2013, Tim assumed the role of Mobile Subject Matter Expert for the Analytics team. Outside of the office, Tim pretends to know how to golf and is a self-declared nerd. Nina Van Brunt stepped into her Analyst role with full force, learning the digital space, training pod members and leading her pod in client communication. She is the Video Channel Subject Matter Expert, serving as the liaison between the AOD Video Team and the Analytics Team, facilitating communication, education and optimal workflow between the two. She also spearheaded the effort to integrate specific video DSP data into AOD’s proprietary SkySkraper database. Nina graduated from Boston University with a BS in Film. VivaKi’s AOD Analytics Team exists to not only evaluate what they find in programmatic campaign data, but why. This dedicated team of expertly trained analysts mines the wealth of data that’s been collected by VivaKi’s SkySkraper data solution for all VivaKi clients across all digital channels to discover actionable insights about audiences and inform optimization strategies. Their efforts result in the development of best practices that advance the intelligence of AOD and, in turn, agencies and their clients. About the Authors

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