Unlocking Location Intelligence for Retail Marketing
This customer story has been adapted from a presentation given at Discovery 2019.
Posterscope: a Location Marketing Specialist
Good morning. First of all, we would like to thank CARTO for all the efforts they have made to promote Location Intelligence in this market. We are very proud to be partners of CARTO and applying Location Intelligence in marketing. We would like to start by making an introduction of what we do and who we are. We are Posterscope, the location-based marketing agency of Dentsu Aegis Group. It is a global communication group that offers holistic communication solutions to brands. At Dentsu Aegis we build communication solutions to innovate the way brands are built. At Posterscope we work with location and help with the location strategy within the communication solutions.
Dentsu Aegis is a global company, with 11,000 clients worldwide, several offices, and 45,000 passionate employees. Within the Spanish group, there are different agencies and we, as Posterscope, are the location solution. In Spain we have 12 offices, more than 70 clients with which we have been building success together and efficient solutions based on location. As we said we are the biggest location marketing agency worldwide and we want to explain our vision and how we understand that Location Intelligence is redefining marketing for us.
We are a communication solution to connect brands with Out-of-home (OOH) audiences in the right moment. Why are we talking about moments? Because we live life in moments, and every moment is happening at a specific location, which normally is OOH. For us it is very important to know and to understand this location because knowing this helps us to develop the most efficient communication solution. It gives us the opportunity to make communication more personal, with context, more relevant to the audience and transactional for the brand. Being relevant is key for us. We will share how Location Intelligence helped us to deliver contextual retail marketing and explain our overall vision in this space.
Contextual Retail Marketing
We believe that retail today is beyond transaction, it used to be the point where you buy products but now in the media ecosystem: activation, engagement, and transaction are closer than ever in any touch points. If I am at a bus stop, waiting for the bus I can buy a product with my mobile. If I am browsing social media, I can buy a product in an ad: every media touch point hosts these things. Retail needs to evolve to something more experiential and for that location and data are key. We usually place retail at the lower funnel in the conversion and when we developed our communication strategy we wanted to generate interest to redirect people to a store. But retail has a bigger role in the knowledge, in the consideration part (the upper funnel in marketing).
Today retail is beyond transaction and inventory and when we talk about retail, we refer to physical commerce because it is our expertise. Our field is OOH and some of the places where people may go is a store and this is where we develop our expertise and solutions. We may think that physical retail is declining because ecommerce is growing very fast but it’s more complicated than that. If we take a look at global commerce figures, we notice that the contribution growth to the global industry is higher in physical commerce rather than online commerce. Despite online commerce growing more, the core business is still done by physical retail. What elements are making ecommerce grow so fast? The convenience is very important but another important piece is the capability to be contextual and be able to analyze a lot of data and interactions from the users to personalize the experience on the whole journey of the website. If physical retail is still growing, can you imagine what we can accomplish when we apply these concepts? This is the level of growth and potential that the retail industry can benefit from.
Relevance is key in marketing
Things need to start moving this way because relevancy is the most expensive element in marketing today. It’s very expensive because there is a lack of attention from consumers, the media is more fragmented than ever, mobile changes people’s behavior so they just look at the ad that adds value for them.
To buy this relevance in a store we would need to use a ‘coin’, in our case the coin would be represented by location data and the currency to force that material would be the engagement. This is what we need to push, engagement is the global currency for buying relevance today. To create this engagement in store we need to build relevant connections based on personal adaptative and valuable communications. For this the way we use location data is key. For us retail is the perfect touch point because one of the harder things is to get the attention of customers. When someone is sitting in your store, you have their whole attention and you need to provide them with something relevant. If we use the information that we have and we can build from the data sources and third-party data we can deliver a better experience. If we manage to make this experience more interactive and more digital we are going to learn a lot more from the consumer and we will be able to personalize that content to build engagement. It will drive an uplift in quality visits, with reference to frequency and length of time in the store.
This relationship is essential and we try to understand what are the factors that can drive these relevant connections and try to build capabilities that allow us to deliver the best communication solutions. The first key for contextual retail is how we can use Location Intelligence and third-party data to understand and build our audiences, as well as personalizing their experience before visiting a store. How can we also discover, by using this data, trigger moments or ‘influence occasions’ when the consumer is in the perfect moment? As explained before, we need to find the relevant moments where we can make a change or we can be relevant to the consumer, this is what we call influence occasions. We also need to deliver connected experiences when customers are in the store, in order to gather data and offer something pertinent for them. Last but not least, we need to be able to create brand data ecosystems as all brands are doing in ecommerce. So we created a platform in partnership with CARTO which is called: Geoxymity.
Location Intelligence for building audiences
Today it is more important than ever to generate different audiences and deliver the most efficient campaign. Recently most people are working to generate these audiences in two-dimensions using digital behavior and context. For us it’s more important to use three dimensions because the physical behavior is very important to understand the geospatial behavior of the people, giving us more accuracy. To target this audience we use aggregated data which is deterministic and declared. We are able to know people’s movements, where they consumed, where they live… We are able to read this data with more granularity, and cross link it with Points of Interests (POIs) in order to understand physical behavior. Today more and more people are using apps to move around the city, to order food delivery, to book accommodation and it gives us a lot of information. All these locations and moments evolve in a context that impacts the mindset and reaction of the people. It is one of the reasons why we built a new technology - XY - which is the first Location Data Management & Activation Platform. With this technology we are able to ingest different datasets, correlate them and identify the areas and moments we want to leverage. With these datasets and the index that we are building, we are able to do audience mapping, geospatial analysis and identify similar locations in another area to create a campaign and have similar results.
One of our automotive clients provided us with several zip codes where they sold a lot of cars of a specific model. We analyzed the audience for these specific areas to discover another area in Spain with a similar audience to launch a digital and OOH campaign. Using this technique the campaign achieved a 230% increase of visitors. We have been using XY with our clients for more than two years now and are constantly improving it and ingesting data.
What is interesting about XY is that there are over ten different data streams connected, some of them in real time with a high granularity of information. We talked about influence occasions to understand what are the occasions or moments which can help us identify where and when we need to impact our audience. First we have internal tools that allow us to understand the audience from an attitudinal perspective: what are the motivations, interest and attitudes. Once we have this analysis, we track those users to understand their shopping behaviors and their routines. From this point we are capable of leveraging all the steps in the customer journey and defining which are the best moments and locations to target this specific customer with very high granularity. We can deliver campaigns like Heineken, that helped us to define the best locations to deliver a promotion to drive traffic to a point of sale (POS). One promotion was to drive traffic to supermarkets and the other one was to drive traffic to a restaurant. We were targeting people with two different mindsets: doing the weekly grocery shopping and having a beer with some friends. This is how we use Location Intelligence to activate an audience and deliver the results.
Video about Heineken Zero Zero’s project and the Out-Of-Home campaign.
One capability that we have in the tool is to build a specific class of audience for our clients in order to target them effectively. When a client has predefined and mapped a persona, we can work with the data and create a specific index to target it. This is what we did for Heineken, by including predefined personas in the platform and understanding how they move and where is the best place to target them.
Another very interesting thing about influence occasion is something that Alexa, Starbucks and Ford are doing. Alexa is configured in the latest Ford cars with a Starbucks skill. For example in the morning, Alexa tells you if there is a Starbucks near your position and if you want a coffee. They are targeting you in a very specific moment because you can order the coffee from your car and go pick it up directly at the shop. This is something really amazing and interesting in terms of targeting influence occasions. Another interesting campaign is the one Burger King did in the US to launch their new mobile application. They sent people to McDonalds and once they were inside (they tracked users through the app), you could order a whopper for a penny.
Another good example of what we did with Burger King was during the Fallas (traditional celebrations in Valencia, Spain) to promote their new home delivery service. It was a good opportunity to launch the service because most of the streets were crowded, it was very difficult to move in the city and the people in the streets would have been very hungry. So we transformed a bus stop into a collection point where you could receive an online order. On one side we were responding to a need from the target and on the other, we were showing that their new delivery service was fast and efficient. It was a fantastic campaign with repercussions in TV and social media, by finding the right locations to deliver the product in the time promised by the brand. Now we have people in the store, we make our brand matters for them, how we need to work towards this?
There are three very important factors when we are talking about physical stores. First we need to make people interact more with us because more interactions help us to better understand people in the store. If we transform the interactions using new digital interfaces we will be able to track everything that is happening. Then, we can integrate this in a brand ecosystem to personalize the content and make our client’s stores more “shoppable”. We did some projects with Coca-Cola and Moët by transforming a traditional channel like a vending machine to a digital channel to increase interaction and information gathering.
Looking at Hellmann’s, they implemented a digital cart that followed customers in the supermarket and delivered specific promotions according to the department. Another interesting example is what Amazon is doing in collaboration with Walmart by implementing a voice assistant system within the supermarkets. When you are in front of a shelf, you will be able to specify your needs, for example: “I need organic food”, “I am diabetic, what do you recommend me?”… With this system, you won’t need to read boxes anymore. This service will be able to gather a lot of information including likes and dislikes but also the emotion they feel by analyzing’ tone of voice. All this data that we can gather is very important to deliver these experiences because interfaces in physical commerce will change to digital ones, screens, mobile, and voice. Ensuring this is organized in the right silos and connecting the different datasets will help us to deliver what we call “contextual experiences”. This capability of gathering and working with data coming from the campaign, CRM, and interactions in the store, allows the building of a brand ecosystem within Geoxymity. This is something that brands need because we are seeing a lot of solutions in ecommerce (Google Analytics, Salesforce…) to work with digital data but what happens with physical stores? How can we deliver better experiences: more relevant and fundamental to people?
Brand data ecosystems
Customer personalization is a driver of growth in ecommerce so we should have a solution for that. Physical commerce needs to be as “smart” as ecommerce to reach this growth and deliver a contextual experience to drive more sales. Today it is possible to collect and activate data from attribution footfall and see what happens in stores. In the beginning the solution we developed was perceived only for local marketing but now it is also working in retail. It gathers data from different sources of information and performs different algorithms to make recommendations of where you should invest more efficiently your local budgets.
There is a video playing about the impacts of artificial intelligence in local based marketing.
Geoxymity is a communication solution that redefines the way that we work in retail and proximity marketing from traditional media planning to that based on audience and real-time data. From activation in traditional format, now we can activate dynamic content triggered by audiences or context in real-time. From traditional reporting measurement to a dynamic dashboard and optimization based on business results.
We build Geoxymity in four modules: one is for management and planning where we can manage and plan all the campaigns that we have in retail and check the results in real time. Then we can activate multi-channel campaigns because we are connected with mobile DSP and OOH signs. We also have a reporting and optimization module where our clients can check all the reports and movements of the campaign in real-time. The last one is intelligence, we are building in Geoxymity, a recommendation and econometric model that optimizes campaigns and makes them more relevant for every local audience. The reporting and optimization also takes into account what’s happening in physical stores, determining what are the metrics or the campaigns that are working better. There is also the possibility to apply other context such as if the weather is having an influence on the campaigns and behavior of the people in the store.
For us a key element for working in communication solutions is to drive relevant connections because it is one of the most important elements in marketing today and it requires contextual content and experiences. To create these contextual experiences we need to personalize every interaction along the consumer journey and ensure we understand all of the specific needs. Everything must be driven by data and delivering contextual marketing requires brands to create brand data ecosystems, not only in digital but in physical also because it’s still relevant in the global retail industry. If we have the capabilities and the technology, we encourage everyone to try and test it.