ATTRIBUTION FOR TV ADVERTISING June 20, 2019 Presented By: BY THE - PowerPoint PPT Presentation

ATTRIBUTION FOR TV ADVERTISING June 20, 2019 Presented By:

BY THE END OF THE SESSION YOU WILL HAVE A step by step guide on measuring attribution for your TV buy. • An understanding of attribution terms and concepts. • A perspective on the relationship between attribution and optimization. • Examples of how real brands measure attribution for their TV buys. •

WHAT WE WILL COVER IN THIS SESSION ATTRIBUTION IN TWO BRAND’S INTRODUCTION ATTRIBUTION IN TV DIGITAL ADVERTISING STORIES Current state Defining attribution • • Class framework • Digital tracking • Tracking TV • Digital attribution • Attribution for TV • Four use cases •

WHAT DOES PHONE RELIEF HAVE TO DO WITH ATTRIBUTION?

LESSON 1 INTRODUCTION TO ATTRIBUTION

WHAT IS ATTRIBUTION? Attribution is the process of: 1. Identifying the marketing events that contribute to a 2. User taking a desired business outcome 3. And assigning value to each of these events

LESSON 2 ATTRIBUTION IN DIGITAL ADVERTISING

DIGITAL MEASUREMENT There two main ways we can measure ad exposure and business outcomes in digital • Pixel : Code on a website that provides notice that a user was on the page. This notice is sent to a cookie. • Cookie : Able to track users across sites and send tracking data to an ad server.

IDENTITY MANAGEMENT There are two methodologies to track and measure consumers across device • Deterministic: Using information such as an email address or login to track consumers across device. • Probabilistic: Using billions of anonymous data points to make a best guess as to which devices may belong the same user.

LESSON 3 ATTRIBUTION IN TELEVISION

MOVING TO ADVANCE MORE METHODS MEDIA MIX MODELING (MMM) is a statistical analysis that estimates the impact of various marketing tactics on sales • and then forecast the impact of future sets of tactics while controlling for a number of factors. MMM USE NIELSEN DATA AS AN INPUT. From the Nielsen’s People Meter, which electronically captures all viewing • from their nationally projectable sample of panelists. GRP: The percentage of an audience that watched a particular spot x 100. Example – A program reaching 25M out of • 100M women 18-49 reaches 25% of the audience. If the ad was delivered 4 times, it would result in 100 GRPs. MMM MEASUREMENT: MMM measures bases sales, the sales that occur with no marketing activity and incremental • sales - The amount of additional unit sales that occur as a result of marketing activities. MMM IS ALSO USED TO DEVELOP RESPONSE CURVES: which help brands understand points of diminishing returns • for their spend.

MEASURING AD EXPOSURE: NIELSEN POST REPORT Report will show when a spot ran, on what network, in what pod, position, etc. X Walking Dead, AMC 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 6 6 6 6 : : : : : : : : : : : : : : : : : : : 4 5 5 0 0 1 1 2 2 3 3 4 4 5 5 0 0 1 1 5 0 5 0 5 0 5 0 5 0 5 0 5 0 5 0 5 0 5 : : : : : : : : : : : : : : : : : : : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 P P P P P P P P P P P P P P P P P P P M M M M M M M M M M M M M M M M M M M

MEASURING AD EXPOSURE: SET-TOP BOX DATA Set-top box captures and stores viewing data.

MEASURING AD EXPOSURE: AUTOMATED CONTENT RECOGNITION ACR is becoming the standard method of measurement for TV ad exposure.

ATTRIBUTION PLAYBOOK q Collect exposure data via Nielsen post reports, set top box or ACR: will come via a direct relationship or via an attribution vendo r.

WHAT ARE EXAMPLES OF BUSINESS OUTCOMES?

ATTRIBUTION PLAYBOOK Collect exposure data via Nielsen post reports, set top box or ACR: will come via a q direct relationship or via an attribution vendor. Make sure you know what you want to measure and have the tracking in place to do q so. It’s best to start with upper funnel metrics.

ONLINE–SPIKE VISITOR ANALYSIS Step 1 : Through a web analytics system, analyze filtered traffic on an hour-by-hour basis .

ONLINE–SPIKE VISITOR ANALYSIS Step 2: Overlay the spots that ran during the time period.

ONLINE–SPIKE VISITOR ANALYSIS Step 3: Develop a mean by calculating web traffic on a minute-by-minute basis.

ONLINE–SPIKE VISITOR ANALYSIS Step 4: Using a 95% confidence level, determine an upper and lower bound to account for variance and uncertainty in the data.

ONLINE–SPIKE VISITOR ANALYSIS Step 5: Measure the number of visits during that spike and back into a cost per visitor metric.

ATTRIBUTION PLAYBOOK Collect exposure data via Nielsen post reports, set top box or ACR: will come via q a direct relationship or via an attribution partner. Make sure you know what you want to measure and have the tracking in place to do so. q It’s best to start with upper funnel metrics. Website Visitation: Track users pre and post spot to understand how running a spot contributes to web traffic. q Develop a baseline and measure incrementality relative to the upper bound of that range. Measure incremental traffic before it reverts to the mean.

ONLINE—SPIKE SALES ANALYSIS Use set top box or ACR data set to get the IP addresses of those exposed to your ad. • Use weblog data to find the IP addresses of users who have purchased on your site over a • set time period. Match those two data sets to find the users who were exposed to an ad and also • purchased. Create a control group to validate your model by using random subsets of the overall • sample. Make sure your control group mirrors your exposed in every way. A / B test for variables such as creative, network and daypart. • Calculate a return on ad spend (ROAS) based on the cost of the spot and number of • incremental users who purchased on your site.

ATTRIBUTION PLAYBOOK Collect exposure data via Nielsen post reports, set top box or ACR: will come via a • direct relationship or via an attribution partner. Make sure you know what you want to measure and have the tracking in place to do so. • It’s best to start with upper funnel metrics. Website Visitation: Track users pre and post spot to understand how running a spot contributes to web traffic. q Develop a baseline and measure incrementality relative to the upper bound of that range. Measure incremental traffic before it reverts to the mean. Website Sales: Track site visitor over time to understand those who purchase. Test different networks, q dayparts and creatives.

TV’s IMPACT ON IN-STORE VISITS Use any of the following to track instore visits • Geolocation Partners: Work with multiple apps to integrate into their • Software Development Kit (SDK) Bluetooth Beacons: Small devices that track users within a retail location • Client App Data: 1 st party app data can also be matched to identity management partner • Match this to an identity partner, who then can match to ad exposure • Develop a cost per in-store visit metric. •

ATTRIBUTION PLAYBOOK Collect exposure data via Nielsen post reports, set top box or ACR: will come via a direct relationship q or via an attribution partner. Make sure you know what you want to measure and have the tracking in place to do so. It’s best to q start with upper funnel metrics. Website Visitation: Track users pre and post spot to understand how running a spot contributes to web q traffic. Develop a baseline and measure incrementality relative to the upper bound of that range. Measure incremental traffic before it reverts to the mean. Website Sales: Track site visitor over time to understand those that purchase. A/B test different networks, q dayparts and creative. In-store Visitation: Using Geolocation, Beacon or Identity Management partners, track users who enter your q retail location and then track that back to an ad exposure

TVs IMPACT ON IN STORE SALES Use any of these methods to track in-store sales A CRM list • Companies such as Nielsen Catalina, which use purchase data and loyalty cards. • (Also IRI, Cardlytics and Shopcom) Credit card companies, such as AMEX, Visa and Mastercard • Use an identity management partner to onboard this data and match to • ad exposure via ACR. Develop a cost per in-store sales metric •

ATTRIBUTION PLAYBOOK Collect exposure data via Nielsen post reports, set top box or ACR: will come via a direct relationship or q via an attribution partner. Make sure you know what you want to measure and have the tracking in place to do so. It’s best to start with q upper funnel metrics. Website Visitation: Track users pre and post spot to understand how running a spot contributes to web q traffic. Develop a baseline and measure incrementality relative to the upper bound of that range. Measure incremental traffic before it reverts to the mean. Website Sales: Track site visitor over time to understand those that purchase. Use this as an opportunity q to A/B test different networks, dayparts and creative. In-store Visitation: Using Geolocation, Beacon or Identity Management partners, track users who enter q your retail location and then track that back to an ad exposure. In-store Sales: Use Identity Management partners who are integrate with Credit Card Parkers, Nielsen and q others to track in store sales.