LEVERAGING DATA FOR BETTER BRAND MARKETING

Transcription

1 LEVERAGING DATA FOR BETTER BRAND MARKETING

2 INTRODUCTION It s no secret that brand marketers have been slow to adopt digital advertising. Until recently, they ve had to rely on broad-sweeping audience buys and indirect measurement to market their products and services. That has changed. Today, digital advertising is a highly attractive medium to brand managers thanks to the growth of fully integrated data-driven buying platforms with realtime learning capabilities. Using a variety of industry, proprietary, online and offline data, marketers can now determine the types of consumers most likely to convert, and focus campaign spend to target ideal consumers. THIS PAPER COVERS THREE USE CASES FOR LEVERAGING DATA TO ACHIEVE SPECIFIC MARKETING GOALS: 1. Increase sales using industry-specific publically available data 2. Prospect new consumers to the brand through lookalike modeling using retargeting (proprietary) data 3. Drive ad-spend efficiency using offline data All three use cases can easily be executed using an integrated platform that combines robust data management and programmatic capabilities. Such platforms can optimize media acquisition, creative selection, and audience buying strategies based on real-time results. DataXu, Inc. All rights reserved. 2

3 USE CASE 1: INDUSTRY-SPECIFIC PUBLICALLY AVAILABLE DATA Goal: Influence consumers in a pre-consideration or consideration phase, when no proprietary data is available for targeting. Strategy: Leverage real-time, publicly known variables (e.g. social, weather- related, heath, etc.) as a leading indicator, and in-store sales data as a lagging indicator. The leading indicators are used to reinforce brand messaging at times when consumers are in or near a consideration phase; the lagging indicators are used to proxy campaign success. EXAMPLES: Tire Manufacturer. If snow or inclement weather is called for in a particular ZIP code or DMA, a tire manufacturer can use this leading indicator to prioritize consumers in the affected areas in its digital campaign. A DSP s real-time bidder is configured to bid more aggressively for those consumers, and optimize message content to highlight safety benefits of its tires. Consumer healthcare company. If pollen counts or cases of the flu surge in a DMA or city, a consumer healthcare company can focus ad spend on those areas, and bid more aggressively for those impressions. Measuring Success: In all likelihood, conversions occur in brick and mortar store. Marketers can study local in-store sales data to gauge the campaign s success. The benefit of industry-wide data sets (e.g. DMA, ZIP code) is they re often pre- packaged, so the brand s marketing and sales teams can quickly and easily put it to good use. It s also more useful than offline data in cases where the data may be unpredictable or can change on-the-fly due to extraneous variables (e.g. weather and health data). REMEMBER THIS By using timely and publicallyavailable leading indicator data, marketers can increase market share and incremental revenue to their brand and category On the whole, industry data is a quick-to-implement and useful proxy when proprietary, brandspecific datasets are not available. Most of the work is performed automatically by the DSP, freeing up marketers to focus on message development and other strategic activities. DataXu, Inc. All rights reserved. 3

4 USE CASE 2: LOOK-ALIKE MODELING USING RETARGETING (PROPRIETARY) DATA Goal: Expand market share by identifying the attributes of a brand s top- performing customers, and then target similar customers at scale. In other words, extend a relatively narrow converter pool into a larger group of lookalike prospects. While direct response and lower funnel marketers have the luxury of optimizing ad experiences to a small group of high value intenders, brand marketers and lead generators do not. Strategy: Use pixels at every stage of the sales funnel to capture data about converters. Pixels can be placed virtually anywhere, including an list, ads, campaign landing pages, and on the website s product, check-out and conversion pages. Pixels are placed prior to the launch of a campaign so the buying platform has a clear sense of what a brand s customers look like, and equally as important, what they do not look like. Advanced prospecting algorithms available through integrated platforms that focus on results-driven/performance marketing automatically optimize towards converter lookalikes. These algorithms examine the attributes of converters and serve ads to prospects that look like them. EXAMPLES: Auto Brand. An auto manufacturer places tracking pixels on its display ad and landing pages, as well as its home, car models and locate a dealer pages. It then builds consumer profiles for each car model and targets similar consumers with the appropriate car model in creative. Consumer Packaged Goods. A CPG brand (e.g. baby goods) places tracking pixels on its landing pages, as well as individual sub-brand pages. The CPG brand is able to track which geographies and audience types shop on its site, and use these insights to target similar consumers at scale. Measuring success: Success is measured by concrete actions (online sales, scheduling a test drive, clicking through to an affiliate channel). REMEMBER THIS Retargeting extension techniques are ideal for brands whose customers signal purchase instant online, either directly via a checkout or indirectly through check-out forms or click- throughs to channel affiliates. Conversion pixels at every stage of the funnel yield important insights to brand marketing analysts. These upper funnel pixels can also be used to scale insights and avoid the small sample size problems that might be found in checkout conversion pixels alone. DataXu, Inc. All rights reserved. 4

5 USE CASE 3: OFFLINE DATA IS USED TO DRIVE AD SPEND EFFICIENCY Goal: Use offline data (e.g. in-store sales data) to optimize marketing spend in the absence of deep funnel online consumer data. Put another way: use retrospective offline data to inform the execution of online prospecting campaigns. Strategy: Offline data sets are mined for rich converter data. In-store sales data, for example, often reveal the attributes that most accurately signal intent to convert. Armed with this information, real-time bidders can assess impressions based on the presence of these attributes, and bid aggressively higher for consumers who match the profiles. Real-time results are fed into the targeting algorithm for optimization purposes. If specific channels aren t delivering anticipated results, the DSP no loner targets them. If local sales data is not available, inventory per store is a safe proxy for serving ads in areas where the products are distributed. EXAMPLES: Consumer Package Group (CPG). CGP marketers examine offline sales data by ZIP code to inform their online media-acquisition strategy. Using ZIP code-level data about current sales, a marketing analyst can order the ZIP codes into tiers of highest performing areas (normalized to per capita consumption). The bidder can then be programmed to bid more in the highest per capita consumption areas of the product, and lower in the lowest probability areas. The result will be higher overall sales in areas that already perform well. Measuring Success: Conversions may occur in brick and mortar store or online. To gauge success, marketers can study local in-store sales data and feed these data into future digital campaigns. The DSP will report all online conversion events. REMEMBER THIS This vision for tracking and attribution online to offline (or vice-versa) is more noise than reality today; however, it is inherently more attainable in the digital world than it is in broadcast television and print, where consumers are measured by GRPs rather than as unique prospects. The future for attribution on CPG and other offline brand marketing campaigns is more promising than ever. Much like traditional advertising channels, these types of campaigns don t have the ability to circularly learn from themselves to improve performance, as the true performance metric usually happens offline. That said, offline data is a great way to prospectively inform digital branding campaigns. DataXu, Inc. All rights reserved. 5

6 FOUR STEPS TO STARTING BRANDING CAMPAIGNS These use cases demonstrate how savvy marketers can take advantage of proprietary and industry data to reach ideal prospects, measure results, and fine- tune their marketing campaigns for increased brand footprint. Following these four steps to focus your next campaign spend on the types of consumers most likely to convert: IDENTIFY YOUR DATA ASSETS Local, publically available data First-party conversion data Offline sales data, by region, store, affiliate MAP YOUR DATA ASSETS TO CAMPAIGN OBJECTIVES Target consumers in or near consideration phase Build your business by attracting new customers to the brand Gain insight into your most receptive prospects Understand best media outlets for your ad spend LINK AVAILABLE USER-LEVEL DATA TO DATA ASSETS Partner with a buying platform with fully integrated data capabilities ITERATE ON CAMPAIGN SUCCESS Leverage learning algorithms that can optimize execution based on real-time results. DataXu, Inc. All rights reserved. 6

7 CONTACT US REQUEST A DEMO INTERESTED IN LEARNING MORE ABOUT DATAXU? DataXu is a petabyte scale marketing cloud that enables marketers to better understand and engage their customers. Powered by Active Analytics, our patented approach to Programmatic Marketing, the DataXu Marketing Cloud is a suite of applications that transform big data into better customer experience at the speed of life. Our software helps marketers focus their marketing investments and achieve optimal results across all available media formats, devices, channels, and buying modes. With thirteen offices in nine countries, DataXu is powering the digital transformation of the world s most valuable brands. Visit dataxu.com for more information. DATAXU NAMED TO THE INC LIST OF FASTEST GROWING COMPANIES IN 2013 & 2014 DataXu, Inc. All rights reserved. 7