WHITEPAPER I-COM GLOBAL SUMMIT 2015 SAN SEBASTIAN: SMART DATA THE VALUE DRIVEN APPROACH

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1 WHITEPAPER I-COM GLOBAL SUMMIT 2015 SAN SEBASTIAN: SMART DATA THE VALUE DRIVEN APPROACH INTRODUCTION: The 2015 edition of I-COM Global Summit in San Sebastian made it clear that marketers in our industry are facing significant, no-way-back changes. Over several days, great speakers and participants led us through the evolution of the marketing landscape and highlighted ways to adapt and embrace it. Many topics were discussed from technology, to data gathering, to data science, to best practices, to people. Most of them addressed the current changes underway from the perspective of a new, value-driven approach based on Smart Data in Action. The great environment and Arzak s gastronomy added a magic touch to it all. This paper recaps the topics covered through participants quotes and insights. It includes a review of the market evolution, along with key topics, challenges and best practices for Data Gathering & Integration as well as Data Science & Action. Thank you for sharing them. EXECUTIVE SUMMARY: Although packed full of diverse insights, the following threads could be seen popping up throughout the 6th edition of The I-COM Global Summit in San Sebastian. Data-driven decisions have become the expectation. Data Science, Technology, Marketing & Business start working together to gather consumer intelligence, inform campaign activation and optimization, and demonstrate marketing effectiveness; yet, still have room to grow to an homogeneous, continuous and massive scale. Big corporations have already started to put in place more dedicated leaders and teams to help acquire, manage and use data more efficiently to make decisions. And successful brands and corporations have started to work with startups and digital companies that pioneer the future knowledge that is required to re-define the recently born data-driven marketing approach. 1

2 Data gathered across devices and platforms becomes the glue to understand consumers and to help build connections with them through their interactions with multiple devices. Social platforms add even more interactions and emotions to a fuzzy network of connected consumers. And mobile, the extended arm of consumers, helps merge digital interactions with real world experiences by bringing moment and location into the stream. Mobile is key for a real personal communication, since it is a bridge that helps turn cookies into people and adds location insight to enhance the consumer experience. The new generation of Millennials, the consistent growth of even more devices, connected cars, and the Internet of things prove that marketers need to evolve to a new way of marketing and to a new way of connecting with consumers. There is a clear evolution to understand the full customer journey, especially in digital channels where most interactions can be tracked. But even only within this ecosystem, data gathering and integration is the first challenge across markets and players. One suggested way to start is with first party data, since loyalty brings higher returns, competitive differentiation, and valuable Intelligence. First-party customer intelligence can be taken into media to follow the customer journey further. And programmatic platforms (or automation of data analysis for media buying and activation) can help with it. Programmatic buying is here to stay; it started with digital media, will be followed by "traditional" media, and will evolve to programmatic multi-channel planning intelligence. Privacy & Sustainable Data Sharing is a must for personal communication to grow; we need to move towards an environment of trust with consumers where reciprocity of value is key. The increased integration and combination of data and marketing science continues to be the underlying story of the Marketing Data revolution. Data Science evolves to the combination of two worlds, traditional Research Methodologies now embed new Digital Real-Time-Discrete data, usually used for optimization. Attribution Modeling is also proving to be a helpful tool for marketers, but for it to grow further, it is important that solutions are integrated within wider marketing, sales & CRM framework. And, in order to create a successful campaign, delivering customer experiences and messages to the right people at the right time, through the right touch point, will require a big dose of CRM strategy expertise in our plans. There is also a need to evolve to more seamless integration of media & data together with efficient and agile content creation. And, data integration platforms and visualization layers that help efficiently and easily understand the impact of marketing activity on business will also help moving to a more data-driven marketing practice. 2

3 SUMMARY OF SESSIONS TAKEAWAYS Market Evolution: Technology and the explosion of devices have completely changed consumer behavior and the way we interact with life. According to Twitter, we are unlocking our phones 100 times a day. In some markets, like Asia, they skipped the massive PC penetration era and went directly to mobile. 25M connected cars today expect to multiply by 4 by PC, mobile, Set Top boxes, Smart TV, Smart Watch, and the Internet of Things become important connection points between people, and between brands and people. New generations coming, Millennials, prove there is no way back on our way to a new marketing era. 85 percent report they sleep with their phones and spend 35 hours per week on digital media, on average. And they claim that the technology that s used by brands is equally important, if not more important, than the messages that the brands deliver. The 360º integrated marketing plans become 365d/24h Omni-channel Multi-device and personal conversations. Or rather a mix. Social platforms are also driving big changes on how to define a successful marketing strategy. Consumers are social; and the boom of social platforms has allowed consumers to do online what they formerly did at the bar, or street, or the local market. And marketers have followed consumers to the social platforms accordingly. We are moving from one video shot campaigns to thousands of contents and messages delivered, yet with the same budget. The way to handle this is to rely on continuous consumer listening and adapt our messages accordingly, including sentiment and emotional tracking. In this environment, CRM strategy and expertise becomes crucial. It s even more challenging in Asia, where you will find five times more platforms than in Europe or the U.S. Data gathered across devices and platforms becomes the glue to understand consumers and to build connections with them. Technology explosion has generated tons of data from consumers interacting across channels, media and devices. Consumers may be moving, changing, and volatile, but we can use the data they generate to understand who they are, where they are, and what they do across media and devices. Most marketing teams evolve to gather this data, use it to make decisions, and to create and deliver interactive content that generates real engagement across all online and offline touch points. But it is not easy in such a fast and fragmented environment. Very good examples where shown during the summit, and these are great first steps to move to a more extended data-driven marketing approach. Mobile becomes the hot spot, the extended arm of consumers; a bridge that helps turning cookies into people and ads location insight to enhance the consumer experience. For consumers, among all other devices, mobile has become the arm extension to live their life in an easier way, ready at any moment to find any information on the move. Location and moment gets critical and mobile has helped enhance consumer experience by merging digital interaction with real world experiences. For marketers, 3

4 thousands of platforms are generating scattered and disperse data without a face. Mobile allows marketers to put a face behind the cookie. Programmatic buying is here to stay; it started with digital, will be followed by traditional, and will evolve to programmatic planning intelligence. Media planning & buying has therefore changed. Today s share of programmatic buying accounts for 15% of total digital expenditure and is expected to continue its rapid growth. Audience seeking (on top of cookies) and A/B testing has become a must. Programmatic digital media will be followed by programmatic offline media such as TV, (which has a three percent share in the U.S), if we address the barriers to embrace it: data integration, commercial model, transparency, measurement, legal/regulation. Programmatic buying will evolve into programmatic planning intelligence. And there is a need to increase agility and flexibility that can seamlessly share data and content across technologies. Data Science, Technology, Marketing & Business start working together to gather consumer intelligence, inform the campaign activation and optimization, and demonstrate marketing effectiveness; yet, need to grow to an homogeneous and massive scale. It is a challenge to gather consumer intelligence in such a scattered and non-homogeneous environment. Adding to that challenge is to be able to use the data in real-time to inform the activation of campaigns on a massive scale. Not to mention the challenge of being able to use the data to demonstrate marketing effectiveness, especially within such a fragmented environment. Insightful and inspiring projects along these lines where shown during the summit. Coca Cola, Kellogg s, Unilever, MMA, Twitter, Annalect among others, demonstrated that data, science, and marketing are working together by combining traditional marketing methodologies with new, high-speed data generation and optimization techniques. They gave very good examples of multi-channel marketing effectiveness analysis and showed as well that there is still some way to walk. Within this complex environment, advertisers also look for the value of marketing, and put in place new roles and structures to evolve to a new value-based model. Technology is available to service marketing. It helps agencies and advertisers with automation and low-value tasks, but also to reach consumers, enhance their brand experience, and therefore persuade them to buy our products. The marketing principles remain the same, but they are now in a more complex landscape. We have the same budgets yet marketing is much more complex to manage, and with more costs. Better measurement and ROI will have to fill the gap. In order to achieve it, Corporations have created new roles (like CMTO - Chief Marketing Technology Officer - or CDO -Chief Data Officer-) and structures, and have also started to partner with technological Start Ups to help introduce new expertise into the traditional marketing practices. 4

5 Data Gathering & Integration: There is a clear evolution to understanding the full customer journey, but data gathering and integration is the first challenge across all markets and players; no one has it all. We want to have the full customer journey to improve our strategies from retention, to upselling, to recommendations, to acquisition to branding. The available data is huge, from socio demo, to location, to response, to consumption, to emotions. But they come from too many different sources, and there are no consistent criteria across platforms. Many initiatives are being taken in order to smooth this required first step, but the efficiencies still need to improve. Leveraging first party data can bring higher returns, competitive differentiation, and highly valuable intelligence. Mass media analysis is very important for most industries and brands. But understanding our own consumers proves to be a source of return, differentiation and knowledge. Hence, a strong focus was put on client profile data, sales rfm data, behavioral data across site or social and devices used. Gathering the data is easier in direct-to-consumer industries like retail or telecoms, but FMCG advertisers can start through their own CRM loyalty platforms (coupons, content), or through alliances with retailers such as Carrefour data offering. We saw several great examples from Desigual, Carrefour, Muji and other players. How to understand the return of mobile and multi-device users, how to use retail data to target at consumers, not media, and finally, how to make it easy for consumers to come to the retailer, instead of retailer searching for them. First-party customer intelligence can be taken into media to follow the customer journey; and programmatic platforms (or automation) need to help dealing with it. Programmatic allows marketers to buy media or audiences on an automated way, like traders. And more easily link first party data with second party (ad serving) or third party (qualification) data and expand the customer intelligence across media. We see big players growing on the agency side, like Xaxis, with proprietary technology and huge cookie inventory, or Digilant, that allow advertisers to create their own DMP and link media to site & crm data. Other strong alliances such as Facebook with Atlas show how easy it is to upload client data and target them through media accordingly, or find other look-alike people through a panel of 1.44 billion users (no worries as a user, you are anonymous). Other advertisers or retailers have opted for Google Audience Manager Stack integrating site analytics, dfp or dbm or for Adobe with its Marketing Suite. Transparency needs to be greater though to allow faster growth. In terms of logic behind, seamless integration with more channels, seamless integration with creative production, and proven return on investment on integrated way. 5

6 For dynamic communication to grow, we need to use more platforms to integrate seamlessly media & data together with efficient content creation, and we also need to apply more CRM expertise to our plans. Programmatic started from the audience buying perspective, but it has to be combined with dynamic creative optimization in order to adjust the message to the audience. The lack of easy, fast & cost-effective creation of content has usually been a barrier to better exploit and take full advantage (ROI) of programmatic planning & buying. New platforms offer a more seamless process, like Kuaizi, a programmatic creative platform that allows marketers to tie ad serving to an efficient and fast content production, or similarly Sparkflow for mobile. It is essential to understand consumers and know what to say to each of them, according to his/her profile, behavior or response to create these personalized campaigns, so CRM strategy expertise becomes a must. Other technologies like Realeyes appear to add emotions & feelings to the consumer data, closing the gap between psychology, math, and personalized marketing. Mobile is key for a real personal communication, since it helps putting a face to the cookies, and tracking the customer journey into the store, or anywhere he/she goes. Great examples where shown from Dstillery, MapQuest and other players that illustrate how location-based data can provide a new dimension to advertisers. First, because of the importance of location when we talk about behavioralbased marketing in the real world. Also, because it helps marketers to be more helpful for consumers, enhancing their real world user experiences. Dstillery tracks data from 6h am to 24 pm, 40Billion d.p. daily, put in context more than 650 places, and 98% audiences are ranked and segmented. People move and we follow, but mobile data also takes us to a new dimension on data volume, ingestion, data quality, management, visualization, analysis, and activation. We can aim to evolve towards personal communication, but we also need to work with mass media communication, especially when most budgets are centered on it or we cannot easily access first party data. The value of building first party client intelligence is clear, but we don t have, and cannot have an ID or first party data for all of the audiences and track them across all the channels. So we need to work with mass media channels somehow differently than with personalized channels. What these channels have in common, though, is that we use them to find the right audiences across media. For mass media planning we will use audience data on aggregate basis or segments that have to be profiled and de-duplicated when you reach them day-by-day or channel by channel to avoid reaching the wrong targets, or exposing them too frequently to our messages. In order to find the right audiences across channels, all research suppliers are moving to Single Panel Sources combined with tracking data (exposure) to profile and de-duplicate audiences across devices. For mass media planning, we need to understand the number of people we reach among our targets, and each new channel or device used is asked to demonstrate, as a start, the incremental reach it provides. The starting point is TV, which includes linear TV, video-on-demand (VOD), and digital TV. From there, they go to extended TV, which is similar to linear TV, but the content is consumed from 6

7 multi-platforms or on different devices. The next stage is total video, which adds multiplatform, digital only video content (i.e. Youtube). Total video is then followed by total view (i.e., text, image, content). Unification and standardization is critical across media, sources and platforms. The alliance between Kantar and ComScore is a proof of significant advances in this line. But the market requires more speed, which is a challenge, since the rhythm of consumers adopting new devices seems to be faster than our capability to integrate them in the established measurement systems. The traditional marketing research methodologies now include more metrics in order to enrich and refine the measurement & planning process, possibly leading to higher growth of programmatic intelligence. Once you reach (or you think you ve reached) the right audience, you need to ensure that your content and messages are seen. In the digital channels, new metrics such as viewability come into play to ensure the ad has been viewed by the audience. Viewability is a guarantee of quality and requires certain industry standards in order to minimize fraud, robots, and the high percentage of ads that can go into a black hole. But other metrics go into the picture such as a certain response, a tweet, a like, a search or a click. And it can move into perception metrics if we have them on a more continuous basis. New commercial models arise. And the explosion of metrics will drive more programmatic planning development. One key difficulty is the lack of consistency of metrics between channels. We rarely asked TV metrics to determine if the people were actually sitting in front of the TV. Yet, it is increasingly demanded in digital. We ll have to see how to create comparable metrics across channels. Advertisers are moving towards tracking a larger number of targeting efficiency metrics as they prove to bring higher return on investment. For example, some advertisers show their best practices by setting the threshold of viewable ads at least +70%, or require an index for intarget, have a weekly frequency control, and non-human traffic under a certain percentage. These metrics are checked across sites and categories as well as private exchanges. Potential movement to Cost per View in Target instead of Cost Per Thousand (CPM) will force the commercial model to readjust. It needs to be figured out with transparency, respect, and in agreement across all stakeholders. New platforms arise to help gather and put all of the data together in a simple, agile way to break the cost-effectiveness barrier. It is an issue to integrate scattered and inconsistent data from different channels online and offline, sources and technologies. And it makes marketers wonder whether it is costeffective to spend so much time on data integration for the value the analysis will bring. In addition to ad hoc platforms that are custom built by advertisers or agencies, new mainstream technologies like Datorama have arrived to enormously simplify the ingestion of data of every kind from online to offline, any source, and achieve savings of +70% on data integration, reporting, visualization, and analysis. Their rapid growth proves again that there is no way back towards a more analytic data-driven marketing. 7

8 Privacy & Sustainable Data Sharing is a must for personal communication to grow; we need to move towards an environment of trust with consumers where reciprocity of value is key. A final, important point to ensure Data Gathering and Integration is Privacy & Sustainable Data Sharing. Governments, legal regulations and society do not make this easy. Therefore, the Reciprocity of value is crucial. We need to be open about data usage and enable consumers to feel more in control. We need to remove friction by using data to give value for every data point collected. We need to facilitate seamless experiences across the digital and physical to drive proactive sharing. We also need to use it more effectively to better target our audiences. If we do, we will evolve to a trust environment: If I trust you, I will give you my data, so you can do everything to make my life easier. Data Science & Action: Gathering all of this data isn t worthwhile if we don t give it a sense and a purpose. It is not about the data, it is about the impact of the data on business. It is a question of asking the right questions, taking the right insights, and showing the impact on sales and overall efficiencies. Clear and simple, make the data shine and tell a business-led story. The rise of disciplines like Data visualization and Data Science to give a sense to data and to make it easy to read, and to decide, will grow further and towards integration. Marketing objectives can range from branding to acquisition to upselling to retention and be aimed at different users and audiences, across channels and devices (pc, mobile, app, set top box, tv, in store ). Tons of KPIs and data are waiting to be analyzed to explain marketing and prove its business value. Marketers either faint or smile. However, data visualization will help get you on your way (there were great examples with mobile data and MapQuest), and data science will help crunch the data and bring it all together so you can make it meaningful. The unification of these disciplines working together with more seamless data integration will make it easier to evolve towards a more mainstream programmatic or automated marketing. Data Science evolves to the combination of two worlds, Traditional Research Methodologies embed now new Digital Real-Time-Discrete data usually used for optimization. Data Science has changed significantly over the last years. Tactical and near-real-time optimization is helped by the digital activation platforms themselves (usually acting upon a limited set of data or channels). But for strategic analysis, the common trend is to use traditional methodologies to give a picture of the whole integrated activity, multi-channel planning or efficiency. Data Science will combine data from different natures and sources (aggregate, static for traditional media versus discrete, inconsistent and dynamic for digital media), and speed is often the big barrier. Some fast steps are shown by technology players that have introduced a layer of traditional data models (science) on top of their generated the data, making it ready to access, and ready to use. 8

9 From a branding perspective, many examples show that digital channels/devices, despite fragmentation, are generating incremental uplift of awareness, engagement, purchase intention, or sales. Many examples were shown on how to use econometric modelling or how to compare exposed versus non-exposed audiences to demonstrate the effectiveness of multi-channel marketing. Mass media traditional metrics are combined with user-experience engagement to show the value of marketing. There are more digital metrics included in the models, such as viewability, incremental reach, likes, tweets, shares, and even emotion index of social users across different channels and devices. Location and time are also being included in marketing intelligence. Panels or retailers offer their data to show the effect on different audiences or customer segments. Attribution Modeling is also proving to be a helpful tool for marketers, but for it to grow further, it is important that solutions are integrated within wider marketing, sales & CRM framework. According to the WFA, more than half of the large global advertisers are already using it. However, the use represents a small part of their advertising spends. For attribution modeling to grow, it s important that solutions are integrated within the wider marketing, sales & CRM framework. All consumer channels and touch points must be included. This will allow marketers to better understand individual customer decisions as well as broad mass media areas for optimization. This is a huge challenge but an exciting one. Analytics / Research shops are combining aggregated offline data models with discrete digital ones to represent the multiple interactions of a full customer journey. Going beyond last-click attribution, we are moving toward explaining how many of the last-click search conversions were actually triggered not only by social, but also TV, OOH or other touch points. And in near real time. But we still see disperse or isolated methodologies. Before even building the attribution models, we need to have all data integrated in an agile and cost-effective way. Some platforms that allow this data integration and move to embed attribution models on the data can help to be faster and cost-effective, such as Datorama for integrated multi-channel data or VisualIQ for digital channels or Dstillery for location-based attribution. But it is not only about Data Science; and it is not only about data science informing creative decisions; it is also about the creative use of the data. Marketing is based on people, and people are based on emotions. Creativity helps develop emotional content. And the creative use of data, put into the context of people s lives can make it more impactful. A brilliant example likes British Airways The magic of Flying by OgilvyOne is worth watching. Data Action relies on people; as we evolve to data-driven marketing, we see more dedicated leaders and teams to help advertisers, acquire, manage and use data more efficiently to make decisions. The focus of most Data & Analytics & Insight teams is on helping marketers do their job better: gather more or better consumer intelligence, make smarter media buys, and have better ways to measure efficiency. In order to create marketing data-driven decisions, there is a need to have a consistent approach on data, products, process and technologies across different departments or stakeholders. 9

10 The key to success is to combine the required skill set: Mad Men and Math Men. A combination of math, technology, business and psychology. There is huge competition for this kind of talent, and a long learning curve. You need to start looking for talent almost a year in advance. And it requires specific efforts to retain and grow the talent. We are seeing more analytics units within media companies or businesses specializing in analytics and the skills are relatively new and complex to find, so competition for talent is fierce. Many marketers want to change the industry and data and intelligence on it is going to be the next frontier. Data Action also depends on company vision and culture; successful brands and corporations have started to work with startups and digital companies that pioneer the future knowledge required. Startups are pioneering the future in terms of digital and consumer knowledge. They are much faster to adapt to the new ways of doing marketing and introduce technology into consumers and company practice, even if some lack clear revenue models. Major corporations represented at I-Com see the opportunity and the responsibility to collaborate with startups to pioneer the future. Bringing David & Goliath together doesn t need to be difficult, as they both have a common purpose and each brings something unique. Successful brands and corporations must be ready to work (partner, hire, invest, acquire, etc.) with startups and digital companies through new, open innovation schemes assumed by the whole organization from top management. Data & Science brings a whole new perspective to marketing. We are facing big changes yet they aren t unlike those we ve seen before in history. For those who like marketing, technology, data, and numbers, there are many fascinating opportunities ahead... For an extended written version of the talks please contact: E: / pjunyentw@gmail.com M: