Mobile Proximity Marketing in France

Mobile Proximity Marketing in France

Location-based data at your fingertips 


LenouvelEconomist run two months ago as a headline, that we moved on to the « Mobile moment ». In fact, Google announced last September that mobile queries had exceeded those made via desktop over the summer 2017 in France.

French actors are clearly lagging behind in terms of brands leveraging mobile to increase conversion but the wind is shifting rapidly and they are on their way to catch up. The main updates and fields of improvement are around increasing the page load times, investing in accelerated Mobile Pages provided by Google, adopting mobile first contents, etc.
On this matter, according to Thomas Husson, analyst at Forrester, this revolution is not only about « a change in mobile usage » but more widely, it is an « evolution of consumers’ states of mind » who want to receive services in real time to satisfy their demands whenever they feel the need for it. In terms of improving customer experience and enabling brand loyalty, he adds that brands should properly perform upstream measures to evaluate the full value of mobile driving in-store traffic, as 85% to 90% of the transactions are still made offline. That is why collecting contextual data link to consumers is key in order to anticipate their needs.


Another key milestone coming this year is the launch of Google’s mobile first index which will impact your overall mobile marketing strategy.Will it become your new SEO Bible? In any case, it will change the whole search result experience giving full credit to the mobile version of your site to rank it on Google. You will need more than ever to understand your users’ behaviour and preferences in order to engage them truly with mobile optimized content and optimized website to increase your mobile conversion rate.


According to the 2018 Baromobile study released by OMD (Omnicom Media Group) together with the expert in drive-to-store S4M, the level of consciousness around « Data connexion » has arised and consumers are using more and more mobile :


Furthermore, according to the 2016 Study made by the Mobile Marketing Association together with L’ARCEP, «  80% of the mobile users receiving a commercial SMS declare themself interested by its content», whereas «  20% among them have already clicked on a promotional link ». So we can ask ourself :

  • Which sms strategies brands are leveraging off to push their in-store conversion ?

For locale acquisition campaign, SMS geofencing is a circumvented tool. Since 2015 in France the commercialization of SMS in client acquisition is rising as retailers and brands want to grow their SMS database and increase conversion. According to a 2016 study, a tremendous open rate reaching 95% (of which 90% within 4 minutes – study from MMA – Arcep) with a memorization rate of 60% (INSEE 2016).

  • What simple content to push ? 

Flash sales notifications, discounts with flash codes,link redirecting toward a landing page, videos. You can as well personalize your sms by creating custom SENDER Id (or OADC) but remember 160 characters maximum and the STOP mention included to be privacy-friendly.

  • How to use geofencing in your SMS geotargeting techniques ?

Retailers are using geolocation as a real life « cookie » to drive traffic in store thanks to GPS, beacons or wifi technologies.  One of the condition using geofencing properly before sending any commercial offer is that you must first get the permission from a mobile phone number to text message them. It can be done through an  SMS keyword sent to an SMS code : « shoes » to 3638 or an optin obtained through a previous campaign. Once customers give their permission to share their location, you will be able to set your campaign and choose for instance a radius of 20km (the maximum distance) around the postal address of potential clients or a radius of 1km around your retail store to reach them.

  • What’s the main advantage of SMS geotargeting ?

It provide you with a high precision target based on past and real time results and, thanks to optimization algorythms, you will be able in the future to consistently improve your targeting audience predicting their needs, their purchase intents while analysing POS traffic and factors influencing them.

Some french specialist in geo profiling and geolocation for retailers like Ubudu  in the tourism industry, can help you building your proximity marketing strategy by providing you with high-precision geolocation features (up to 10cm !). You will be able to send push notification according to their location, send them personalized welcome message, enable customers to avoid lining in store and enable them finding products and services as fast as possible to provide them unprecedent experiences !

  • Toward an omichannel strategy ?

Click and Mortar and pure players businesses are leveraging consistently the mobile experience to fuel their omnichannel strategy by multiplying acquisition campaigns and activations. Sephora is a good example of a makeup store retailer using sms within its 360° « Wonder » Christmas campaign and whom has been recently rewarded for it (read the dedicated article here).


Mobile is key when we think of cross-canal and ROPOiste strategies because acccording to the 2016 study of L’Observatoire du ROPO², on average out of 100 visits in a retailer store (during a period of 3 months), 46% of visitors are cross canal (visiting the website and the store) and conversion rate made via mobile in France is reaching 56 %. That is why, brands should perform various drive to store activations such as Drive to store RTB, Facebook Offers or SMS.

Lets focus on mobile display advertising wich offer huge potential in terms of activating local customer :
→ You can stimulate real time visits in store by targeting precisely your customer catchment area. Plateforms such as Adsquare, which is a mobile first data exchange, allow you to broadcast custom offers based on contextual information (open hours, weather, events and dedicated locations), within where you can adjust the radius of your reach and add advertisings redirecting to Google Map.
→ One insightful business case is the partnership made between the french adtech startup Databerries (now Teemo) and Intersport around its « Real life targeting » solution. It includes a SDK (a set of programming tools for your app), integrating easily geolocation data from 40 app publishers (including Marmiton, L’équipe). For Intersport, a « visit » is equal to a 15 minute visit in store. Thanks to Databerries, Intersport confirms that for one euro invested, it take back 4 to 6 euros margin (study available here)
In terms of your overall customer journey, what could be the next steps once you have attracted potential customers in-store ? Leveraging in real-time your data collected is essential :

2/ During the visits :

  • In-store wifi : accessing the free In-Store wifi access to identify your visitors and activate marketing trigger (push notifications, trigger content on wi-fi connection landing page) to collect data and new optins
  • Geofencing local notification

3/ Post-visits : Behavioral retargeting
By collecting  of individual data visits and sending :

  • SMS / Email offering complementary/lookalike products
  • SMS/Email to encourage revisiting the store with a welcome back message



Transforming your store into a « Data Generator » and enhancing your database plateform in order to serve your drive to store and omnichannel strategy is the way to procede in order to boost your sales. Retailers are in this way tending to adopt the « Cookie less » targeting model thanks to the unique identifiers.

→ A great variety of first party location data is now at your disposal like the Mobile ID (MAC Address), Mobile Number and optin thanks to the synchronisation between a device having a unique identifier and emitters like wifi sensors, IoT signals, GPS, beacons. You will be therefore able to cross historical location data, detailed behavioral pattern, as well as intentionist data within the same place. Adtech technologies are rightly improving their capacities offering now Location-smart SDKs. On the media buying plateform side (DSP, DMP, trading desks), french actors are doing more and more partnerships to access millions of unique ID, combine it with online identifiers and geolocation data. For instance Vectaury is coupling its DSP with its SDK to propose ultra qualified segmented audience and thanks to different partnerships with Mondadori, Madvertise,  they have access to more than 10 millions located user data that they propose to publishers to maximise their conversion.

«  Mobility data » as it is called, has become therefore a new source of information and is used as a proxy for second and third party engagement data (read the article here).
For instance, Fidzup can provide you a clear measurement of your Drive-to-store ROI by performing behavioral targeting in and out of the store (buying intention, catchment area, competitors customers) and is able to collecte granular data coming from Store, section, fitting rooms, floor, cash registers. (To know more about Fidzup : here).

However, in order to ensure clean and high qualitative data origin, your mobile advertisers must cross-referencing location data through different sources. Examples would be using GPS, phone operators, beacons or specific algorythms and detect any possible ad fraud in order to collect compliant and qualitative actionable data. On the compliance part, the french mobile actor Vectaury is offering a new optin since the beginning of 2018 : a « Geo-transparent optin »banner to simplify the consent collection of mobile users and perform anonymized profiling (read article here).
As a matter of fact, the overall marketing need to collect contextual data is becoming widespread and confirmed by the last trends in the Adtech market. Since the beginning of the year 2018, the first Adtech sector attracting investments in France is the Drive- to- store sector. French actors like Teemo (Ex Databerries), Mozoo,  Vectaury or Fidzup are leveraging offline market opportunies given the fact that this market is not under the Google and Facebook dominance. For instance, the French Actor Tabmo is trying to make the usage of mobile DSP more accessible to agencies accompanying brand thanks to its creation module : « GPstore (drive to store),  MScroll (canvas type) and the SlideMotion (read the article here).

It is no more a question of proximity advertising but about the unicity of the location data that lead to new marketing strategies : Online to offline attribution, retargeting and re-engagement. What is important to keep in mind is to leverage on your CRM data and – onboarding thanks to  cross-device data combination. According to Ray Kingman, CEO, Semcasting «  By using IP, location and device matching, marketers can leverage mobile to execute deterministic attribution with 70%-90% coverage matching across all channels and platforms – both online and offline».

New marketing metrics are therefore emerging to mesure the online ad impact on offline sales with KPIs such as :  visit rate,  Cost-per-Visit (CPV), visit direction, number of visits, areas visited location intelligence:

To go further on the metrics subject, earlier at the Mobile World Congress hold in Barcelona (from the 26st of Feb until the 1st of March), the company Augury took the opportunity to publicize its first complete app ecosystem intelligence solution by launching «  Active Insights »which combines cross-app data and provide full cross device reports . The Ogury mobile data collection plateform has data from more than 400 million users with audience segments based on the mobile users app usage. It give marketer competitors insights, how to deal with churn rate and  how to segment their target to deploy mobile ad targeting then outside the apps which hit an unprecedent scale in terms of insights.


After casting a wide net around mobile strategies.. what if blockchain was coming into play ? Mobiquity Networks, a mobile  location data intelligence provider adopted a blockchain layer into its marketing strategy. Its plateform gathers ID, IDFA (Apple Identifier) with anonymized location data (like footfall traffic in-store) via third-party permission-based mobile apps, primarily shopping apps and combined with other data in order to be sold to clients. Adding a hybrid blockchain layer to your database can help your business dealing with your data separation problems providing structures to guide your data pointers and breakdown each « event » within your blockchain together with IDs source written into it. Blockchain is therefore an extra key consideration to not underestimated in the digital marketing and advertising data management landscape.

To conclude, drive-to-store strategies on the marketing as not yet entered into a mature stage has its overall impact measurement (whatever the device used) is still not entirely manage by measurement companies. The latter are trying to provide real time insights to measure the entire online and near/in store customer journey that will allow brand to perform hyper locale marketing campaigns. The advent of contactless mobile payments is another factor that is going to reinforce the practice of real time targeted actions as well as analysis based on these new consumer behaviour shopping habits.

Therefore, the « mobile-ization  » amongst retailers and pure players brands is on its way in France, blending greater ease and convenience of shopping experience for mobile users and customers looking for greater on the go experiences.




Mobile Proximity Marketing in France

Giving better attribution to your Marketing Measurements

Going into the 2018 Spring and aspiring more than before to make disruptive marketing campaigns ? As a marketer, I understand the excitement of being at the front row of the frenzy scene of voice recognition, programmatic ads, working with micro influencers and testing AI powered solutions to create content and provide tremendous website experiences to increase your conversion rates…But yet,  are you still relying on the last click model ? It’s time to reshape the way you measure your overall marketing spendings across all channels to evaluate your real ROI and take strategic decisions accordingly.
What it is said on the field on this specific topic ? Listing of existing marketing attribution models and tools as well as some examples of companies who decided to implement models measurements will be provided to you in this article, leaving besides detailed demo calculation which rely later under your jurisdiction.

Figures and quotes to begin

Back in 2015, a Google blog’s post entitled The path to better measurement : Analytics and attribution already set the tone  « Think of attribution as the peanut butter to analytics’ jelly. Yes, each is great on its own, but for many, they’re even better together ».

As stated by a French source (L’ADN), 2017 was the year of « Predictive Marketing » with the culmination of testing and development of new algorythmic attribution models.
In fact, changes in digital spendings have been observed in the past year among large-scale companies : P&G cutting off $100 million dollars eliminating unprofitable ads and seing no decrease in sales, whereas L’Oréal did the opposite increasing its expenses to maximize its digital returns (as detailed in the Fospha’s article : Top 6 Changes in Marketing Measurement that will Impact 2018).

How will the 2018’s measurement landscape look like? It will be the year to change your digital budget, because according to the Demand Gen Report’s 2017 Marketing Measurement And Attribution Survey Report : « 91% of B2B marketer agree that marketing measurement and reporting is a top priority for their organizations » and « almost a third of marketers do not even measure their contribution to revenue, and fewer « 14.8% say they contribute to more than half of company revenues ».


Existing Attribution models and brand measurement examples

So based on these facts and as detailed in my previous article : Is Customer Data Platform the new DMP ?, we can confirm that the marketer’s graal is to get an holistic view of the consumer journey by adopting unified plateform technologies leveraging structured and unstructured data and integrating attribution modules (measurements based on trackable online interactions like clicks) to exact audience targeting and optimize the overall media ROI.

The last click model was still used by 79% of french advertisers for assessing their marketing performances (2014’s IFOP study) . This single touch model, gives all the credit just to the last touchpoint of the consumer and tends to overweight the paid search lever among other things. Only a part of your real marketing cost is evaluated, you may not have a margin but instead an overall loss. To understand the limits of the last click model here a thorough and clear explanation given by Jerome Sutter’s slideshare : Le Last-click, c’est paléolithick ! 

New attribution schemes called Multi-touch Attribution Models are the measurements to be used in 2018 ! 47% of marketers using MTA said that they were using the right model (according to the 2016 State of Pipeline Marketing Report). Here you will find the different models that you can setup if you have a Google Analytics account :

Linear : assign an equal share in conversion to every channel. It is often used for long branding exposure

Time Decay : time-based giving more credit to recent interactions than older ones : shorterm.

Position based : greater conversion value is given to both first and last click (40% each) with 20% that is attributed to the rest in between middle

Custom attribution model : to create your own hypothesis and test it

For instance, AccorHotels has declared in June 2017 that the group was tending to not use anymore the last click model to be in line with there ecommerce acquisition strategy. They were using at the time the Last Click Model with an attribution window of 30 days and on the Display part the 48 hours Post View Model (Think with Google’s article Comment AccorHotels pilote sa stratégie d’acquisition e-commerce ? »).

The International Jewelry brand Pandora decided to increase its digital investment by 46% in 2016, therefore in order to follow that new strategy, the company had to change the way ROI was calculated to optimize media spending. They have accordingly started an attribution project in collaboration with the Mazeberry’s Attribution Solution : performing A/B testing, activating 18 levers, and getting a 360° vision of their marketing mix. They multiplied their profitability by 6 for the Retargeting, by 2 for acquisition emailing and by 4 for Display RTB media ! (Pandora’s business case available here).


About metrics and publisher solutions

Ready to use these models ? There are different web publisher solutions on the market that offer attribution sections such as Commanders Act, known as Tag Commander with its Mixcommander product, AT Internet with its Channel Optimizer tool, Convertro providing MTA and mobile attribution solutions, Impact Radius platform giving omnichannel insights with its attribution reporting. And of course the Google free and easy to use Google attribution modelling solution whom has been launched in may 2017 and still is in beta version (the advanced and paying version is Google Attribution 360).

As already explained in 2016 in the Forrester Wave™: Marketing Measurement And Optimization Solutions, Q4 2016 Forrester’s research recommends to adopt a unified marketing impact analytics UMIA » it goes further as it includes the impact of all marketing media and efforts as well as other more economic variables such as variation in prices.
So there is a need to still use independant metrics that can be complementary to not solely rely on a one side vision of your performance metrics !

Additional challenges to consider

Measuring your cross-chanel and cross-devices performances is challenging as it’s difficult to fully track print left by consumers on their journey to purchase your product. Brick and mortar businesses with online and mobile application for instance, can face difficulties linking their online and offline activities to know exactly which online channel was used to drive in-store revenues.  Wifi, bluetooth beacons but also.. word of mouth, reputation and other factors come into play to influence the final purchasing act. Google and Salesforce have recently joined their forces to enable GA360 clients to « integrate online and offline customer touchpoints » as Mark Benioff, CEO of Salesforces (remark compiled in the previously cited Fospha’s article : Top 6 Changes in Marketing Measurement that will Impact 2018).

Organizational structures can still slow the implementation of these new metrics, as according to the research undertaken by the Data & Marketing Association and the Winterberry (stated in another Martech’s article Forward thinking: Reshaping how Marketers View Campaign Attribution) : « More than 35 % of surveyed marketers believe inherent organizational structure issues the tendency for companies to deploy little to no unified strategy to oversee marketing performance complicate attribution efforts ». Furthermore, GDPR is more than ever here to tickle you with its restriction on consumer data and the way we collect them (clicks collected through cookies), a reminder provided in the The disruption of attribution is coming MarTech’s article. And on top of that, which place will take AI and intelligent agents on the customer journey ? How will machine learning will attribute a sale when the purchase will be made by algorythms and not by the consumer itself ? (mentionned in the following MarTech’article).


Takeaways for marketers : There is a multitude of attribution performance measurements.(tons of articles like Beginner guide to Google Analytics Modelling or how to do Conversion Attribution modelling are exploring the subject extensively). Either, you have more the detective Del Spooner (Will Smith) profile in I robot mistrusting innovative technologies or on the contrary you are too much engage falling in love with an AI as Theodore Twombly (Joaquin Phoenix) in Her, do not go nuts and take time to think about what its really bests for your business to increase conversion. Tests measurement models and choose the one adapted to your audience and your strategic objectives to be better data-driven focused. And then time for testing, implementation and constant experimentation ! A wonderful journey that never ends 😉

BIG DATA & CRM : Is Customer Data Plateform the new DMP ?

It’s a question that should have already arouse your interest as a marketer. Why ? These last few months have been fueled by discussions, talks and market moves around that technology stacks called Data Management Platform. There is a shift in the data-driven approach to collect, activate, and analyse data. Have you felt it coming ?
Indeed, lately at the Boston MarTech Conference (2-4th October), the question about « Finding success and efficiency from a centralized customer data center » so in other terms, the « rising of the Customer Data Plateform », has been one of the main focus. It directly relates to the DMP tool which has been mostly used until recently to maximise media audience activation by tracking user navigation. The today’s need is to get an holistic view of the customer in order to drive loyalty and enhance customer lifetime value at a larger scale. The AdTech and MarTech industry’s aim is to gather as qualitative PII and non PII data (Personal Identifiable Data or not) as possible and make a greater use of the DMP. So what about Customer Data Plateform, is it really new ? What has been done so far on the market ?And why as a marketer should I bother reading this whole article ? Well, there is no promises just facts to provide you with a close-up of the major challenges around data management which is impacting the entire digital ecosystem, including you !

A Data-driven perspective…

Let’s get a clear understanding of what a DMP is, its evolutionary applications and the avent of a « Data Customer Plateform » vision.

According to Forrester Research, DMP is a « unified technology plateform that intakes disparate first-, second and third party datasets, provides normalization and segmentation on that data and allows a user to push the resulting segmentation into live interactive channels environment». This technology stack has been used for the past eight years to mine the data originating from Big Data. The flow streams stored is a combination of first party data, the most valuable assets including brand’s audience, media, browsing and mobile data (options, visited pages, clicked on banners,etc.). Second party data concerns partnering agreements and third party data are data collected and sold to other companies for audience targeting.The particularity of the DMP tool is that it gathers mostly non PII information and therefore differs from a data lake technology which is reserved for internal use (example of the Hadoop ecosystem).

In what extend are marketers concerned ?

As a marketer you certainly realize that data is a key financial asset that is at the center of your marketing strategy to get a competitive advance on the market.
Using data management technology has became a standard tool to score in real time users across every channels and touchpoints. In order to leverage your DMP you have to build actionable and valuables segments by collecting behavioral data. Your segment strategies will then serve different purposes : activation of new leads, use of look alike modelling for finding new customers, consolidation of data by user-matching, qualification of cookies and the performing of analytics.
Moreover, accepting to perform peer to peer data sharing with publishers can also contribute to maximise your media strategy targeting more high-end audiences. It will contributes to lower your CPA (marketing sales and costs for acquiring a new customer) which is a key indicator of a successfull marketing campaign.

Issues and challenges around Data Management

According to the study entitled « DMP Europe 2016 » led by Exchange Wire, Weborama and Stratégies, 37% of the companies equipped with a DMP technology complained about the few concrete marketing activation possibilities (sending emails, custom contents). The DMP tool is rather under-used because at its origins it was created to monetize data through programmatic display buying. Thus, people are undervaluing its scope of application. Moreover, the Converteo study highlights the fact that in France, the use of DMP is not totally common among companies.
Another issue about DMP concerns its scaling limits : if the plateform does not drives enough media buying volume, the DMP is not a « good value for money ».

The avent of the Customer Data Plateform vision

That is why there is a shift today on the market because agencies and brands want to fully embrace a data-driven strategy and converged toward a single plateform that integrate solutions : DMP behavior data with CRM data. They are building what we call « Consumer data Plateform » which is a unique solution relying on a single identifier for each customer to operate on a larger scale. The marketing Analyst David Raab introduced this trending acronym «Customer Data Plateform » back in 2013 to explain the need of global companies to link big data and data insights. The Customer Data Plateform is similar to marketing hubs and designed to centralize and store all type of customer’s data contrary to DMP solutions whose Data stored (First, second and third party data) is anonymous. According to Cyril Fekete, consulting director at a french specialist called Artefact, CDP corresponds to the following formula : « CDP = DMP + CRM + data lake ».

A broad application scope and a promising future

As Emily Macdonald, the head of programmatic at DigitasLBi said, there is a « march of martech » where big players in Saas are moving and acquiring DMP, CRM and automated marketing solutions : Salesforces with Krux DMP, Oracle with the Eloqua Marketing Solution or Adobe with the Neolane CRM tool (look here at the Gartner’s 2017 Magic Quadrant For Digital Marketing Hubs).
On the French market, different companies such as the Eularian or Makazi startups have already broaden the applications scope of the DMP with the activation of browsing information through emailing.
Another reason for using such technology stacks is that marketers and data owners want to better deep dive into data to get greater return on assets. They want to trigger purchases and increasing retention among their targeted audience by enhancing their customer knowledge.
However, it also means that data owners want to have a better control of their own data to optimize their marketing ROI and manage price setting with publishers and other ad tech players partners. In fact, their is a need for transparency around the use of data (what is shared) and its business model (fixed price, CPM,…) as in the past there were no clear rules (cf. AdExchanger article) and there is always a privacy risks around hijacked cookies.

But what about the impact of the GDPR’S Directive ?

All theses changes and need of transparency are linked to the General Data Protection Directive and Eprivacy Regulation that are coming into play in May 2018. They are going to sweep off the opaque layer of privacy and impose rules to protect users from data misuses coming from the entities responsible of personal data collection. The EU Commission wants to end cookies’ headbands displayed each time a user visits a website and replace them by a unique consent given directly through the browser settings. It means that a user can reject all cookies at once. That is why the draft regulation can have a huge negative impact on the advertising industry and might slightly change the game’s rules.

So what’s next ?

Hence, there is a lot going on around Data Management ! The future of marketing stacks includes for sure the Customer Data plateform which is a reflexion encompassing a unified omnichannel vision with on and offline data.  DMP technologies are not finished yet as its applications have not be fully exploited on the market. Furthermore, advanced artificial intelligence, machine learning and cloud computing will play a great role in data provisioning, storing and analytics. So, whatever the name chosen to call your single data platform management, opt for a solution that merges all cross-device and cross-channel customer data and favour the individual’s customer journey. As Paul Graham said, your goal as a marketer is to « make something people want ». Let’s enrich and leverage your data in order to better engage your audience, increase conversion and maximize your customer lifetime value metric.

What is your viewpoint about this topic ? Share your thoughts with us right here .

BIG DATA & CRM: Is Customer Data Platform the new DMP?

BIG DATA & CRM: Is Customer Data Platform the new DMP?

It’s a question that should have already arouse your interest as a marketer. Why? These last months have been fueled by discussions, talks and market moves around that technology stacks called Data Management Platform. There is a shift in the data-driven approach to collect, activate, and analyse data. Have you felt it coming?

Indeed, lately at the Boston MarTech Conference (2-4th October), the question about « Finding success and efficiency from a centralized customer data center » so in other terms, the « rising of the Customer Data Platform », has been one of the main focus. It directly relates to the DMP tool which has been mostly used until recently to maximise media audience activation by tracking user navigation. The today’s need is to get an holistic view of the customer in order to drive loyalty and enhance customer lifetime value at a larger scale. The AdTech and MarTech industry’s aim is to gather as qualitative PII and non PII data (Personal Identifiable Data or not) as possible and make a greater use of the DMP. So what about Customer Data Platform, is it really new ? What has been done so far on the market ? And why as a marketer should I bother read this whole article ? Well, there is no promises just facts to provide you a close-up of the major challenges around data management which is impacting the entire digital ecosystem, including you!