WO2018130505A1

WO2018130505A1 - System and method for managing relations with clients present in a connected space

Info

Publication number: WO2018130505A1
Application number: PCT/EP2018/050410
Authority: WO
Inventors: Nicolas SMET; Cyril SMET
Original assignee: Openfield
Priority date: 2017-01-12
Filing date: 2018-01-09
Publication date: 2018-07-19
Also published as: FR3061791A1

Abstract

This system for managing relations with clients present in a connected space or outside of said connected space comprises a set of points of physical contact or outside of the connected space (P1, …, Pn), for some geolocated in the space, capable of collecting information relating to clients situated in information collection areas, a platform for synchronous or asynchronous collection of these data and means (I) for storage and organisation of the information, in particular geolocated information, means (II) for analysing and displaying the data stored in the storage means and means (III) for using the analysed data for performing determined actions, in particular but not exclusively on the basis of analysed geolocated and/or behaviour data.

Description

System and method for managing relationships with customers in a connected space

The present invention relates to a system and method for managing the relationship with customers present in a space, such as a space containing retail businesses, shopping center type, a sports stadium, a park of exhibition, or a theater, a leisure center, a cultural center, a train station, an airport, a hotel, ...

Such a space can be an open or closed space, delimited or not delimited.

Of course, it is not beyond the scope of the invention when it comes to ensuring the management of the relationship with customers in other types of spaces.

Thus, for the purposes of the present description, the term "customer" means any type of user located in a public and / or private area and likely to use, consume or purchase products or services, or to participate, as a spectator or visitor, at an event presented in public.

We also mean, by customer, any type of user who interacts with the space in which he is located and / or who performs a consumer action of a product or service and / or who participates in the activity of the place.

But the invention also finds an application for managing the relationship with customers who access products or services or the o ffers of products or services, and / or digital content from, for example, the Internet .

Customer relationship management tools are typically used to collect and analyze customer information to provide action based on the information collected.

It may be, for example, to acquire customer information to improve the knowledge of customers' needs for respond to change the relationship between a supplier and its customers.

In this respect, the offers of products or services can be adapted according to the information provided to offer personalized services, both in terms of content and rates.

In addition, some customer relationship management tools are able to change the behavior of customers. For example, one can launch targeted marketing campaigns to build customer loyalty or solicit interest in a new offer.

CRM tools are typically referred to as CRM. They are designated by the Anglo-Saxons by the term CRM (for "Customer Relationship Management").

GRC management tools implemented in connected spaces are generally limited to a collection of information resulting from the counting of customers in predetermined areas, for example in access roads to shops or near shop windows, or result from the detection of people connected in wifi to terminals of access to a telecommunication network.

The management tools imple- mented so far in connected spaces are thus inadequate to acquire data rich enough to implement effective management of the customer relationship.

In view of the foregoing, an object of the invention is to provide a customer relationship management tool capable of providing improved customer relationship management by providing enhanced customer characterization.

The object of the invention is therefore, and according to a first aspect, a system for managing relations with customers present in a space connected to or outside said connected space, comprising a set of contact points able to collect information relating to customers located in or outside of these areas of information collection, and potentially geo - localized in space, a platform for the collection of such data, means of storage and organization of analysis and viewing the data stored in the storage means and the means for using the analyzed data for executing specific actions.

Such a management system, which makes it possible to acquire information from the points of contact for certain geolocalised in the connected space, and to analyze information, thus allows an enrichment of the data of the customers and thus to implement geo-contextualized actions or business processes.

For example, the analysis means comprise indicator calculation means, at least a part of which is intended to trigger predetermined actions, from the data collected.

It can be provided that the management system includes means for input of data external to the connected space, the means for using the data and the means of analysis being adapted to jointly use and analyze the external data for the data. execution of those actions.

According to another characteristic of the management system according to the invention, the analysis means comprise a predictive module able to predict a behavior of the customers.

According to yet another characteristic, the management system comprises analysis means comprising means for correcting and correcting the stored data.

Advantageously, the system comprises means for calculating a representation of the connected space.

It can still include means for the transmission of messages to client users.

In one embodiment, the management system comprises means for calculating predetermined action triggering parameters, said parameters comprising at least one parameter chosen from behavioral and / or geo-localized parameters, information collected from points contact, information external to the connected space, and / or information related to uses of services offered to customers. Preferably, the storage and organization means of the geo-localized information comprise a storage memory of big data, relational data storage means and a cache memory.

The object of the invention is also to provide, in a second aspect, a method of managing relations with clients present in a connected space comprising a set of geo - localized contact points in the space, in which:

- information about customers located in information collection areas is collected;

- Organize and store localized information;

- the stored data is analyzed, and;

- the analyzed data are used for the execution of specific actions.

For example, actions are determined from behavioral and / or geolocated data.

Other objects, features and advantages of the invention will become apparent on reading the following description, given solely by way of nonlimiting example, and with reference to the appended drawings in which:

- Figure 1 is a block diagram illustrating the general structure of a relationship management system with customers according to the invention;

Figure 2 is a detail view of the system of Figure 1;

Figure 3 shows an embodiment of the system of Figures 1 and 2;

- Figure 4 shows an alternative embodiment of the system of Figures 1 and 2;

- Figure 5 illustrates an example of application of a system and a method according to the invention;

Figures 6a to 6f illustrate another application of a system and method in accordance with the invention; and

- Figures 7 and 8 illustrate another embodiment of a system and a management method according to the invention. Reference is first made to FIGS. 1 and 2 which illustrate the general architecture of a customer relationship management system according to the invention, designated by the general reference numeral 1.

The system 1 comprises three platforms I, II, III that cooperate to collect, organize and analyze data from customers who are present and circulate in a physical place, in this case a connected space.

In the following description, it will be considered that the connected space is a sports stadium or a shopping center. But such examples are in no way limiting and other applications are possible without departing from the scope of the invention.

The first platform I is a data collection platform for users present in the connected space to deduce physical and / or digital behaviors.

By digital behavior is meant behavior in a digital environment, when using digital tools. This is, for example, navigation when accessing a website, the use of a mobile application, the behavior of the user when accessing social networks, ...

Note also that the collected data can be collected in real time, that is to say synchronously, or collected asynchronously, deferred.

The platform can also ensure the collection of data outside the connected space.

This platform I communicates with a network of contact points PI, P2, Pn which are for some geolocated in space.

These geolocated contact points are in other words located from a coordinate system. It can be various types of contact points, such as wifi access points, proximity or "beacons" sensors, local merchants, loyalty terminals, ticketing systems, terminals parking, interactive terminals, ... They are intended to retrieve information relating to the customers with whom they interact and which are therefore located in areas of contact information. The nature of the information depends, of course, on the nature of the points of collection. Thus, when it comes to points of sale, this information may in particular relate to purchases made. This information may also reflect the presence of an individual or type of individual in an information collection area. They are sometimes combined with location data. They can also be anonymous or nominative.

The format I is intended to ensure the recovery of these data and to prepare them for use in the other platforms II and III.

As can be seen, however, these data are enriched from PE data from outside the connected space. Any type of data can be used to enrich the data delivered by the touchpoints according to the future use of the analyzed data. This externally derived data may be meteorological data, event data, or any other type of data that can be used to expand the contextual fields of the analyzes.

The second platform II is a platform for the elaboration and reporting of performance indicators, which is intended, in particular, to measure the performance of marketing and sales actions.

The platform II is intended to present the collected data, to render the analysis of the collected data, and to measure the use of the place and the performance of the communication, commercial and / or marketing actions in the place.

Third Platform III is a customer relationship management platform or "GRC" platform that provides targeting and campaign management. It aims to deliver in the best possible context the best proposal on the most relevant support for each client visitor. FIG. 2 shows the detailed architecture of the three platforms I, II and III.

It should be noted, however, that platform III is based on a standard CRM analysis tool. Its description will not be detailed later. However, it will be noted that its functionalities are increased in the context of the present invention insofar as it makes use in particular of geo-localized contextual data.

With respect to the first data collection platform I, this includes a first data collection stage 2 which communicates with the contact points and retrieves data from outside. A second communication stage 3 implements a set of exposure services making it possible to make the processed data available to external communication systems.

The stages 2 and 3 thus constitute stages of input and output of data.

In particular, the data retrieved from the contact points are data used to characterize the customers present in the connected space. For example, this data can be of the type:

- behavior data;

- consumption data;

- socio-demographic data;

- location data;

- usage data;

The platform I further comprises a layer 4 of data storage. This layer 4 comprises a cache memory 5, which allows fast access to the stored data, a big data base 6, allowing the storage of vo light and unstructured data and a relational database 7 in which is stored the data set Collected, corrected, calculated and used by all the various stages of Platform I, other than Stage 2. Finally, the platform I comprises a calculation stage 8 which analyzes the data stored in the data storage layer 4.

This calculation stage comprises, firstly, a predictive engine 9 which makes it possible to predict customer behavior from the stored data, a module 10 for analyzing big data, a calculation module 11 in which specific algorithms related to the data are loaded. sectors, locations and trades concerned, and in particular specific algorithms related to geographic data and geometric locations concerned, and to view the data stored in the layer 4, and a module 12 for calculating communication action triggers , commercial and marketing.

The calculation modules 10, 11, 12 are intended to calculate business indicators or parameters intended to trigger predetermined actions.

For example, you can decide to send a marketing campaign to a selection of people who are expected to come to the connected site to encourage them to come to benefit from a commercial action. This operation will itself be triggered when detecting the presence of people targeted on the site.

These modules 10, 11 and 12 of calculation elaborate parameters that can be used by the upper layers.

They are also used to correct the data obtained according to the source repository.

They incorporate, in this respect, filtering and error calculation means and are, for example, adapted to eliminate outliers, and to assign weighting coefficients to the data coming from the collection points.

Thus, for example, the recovered data that is geolocated outside the connected space is not exploited.

These modules also calculate business indicators that are determined to be of interest to the end user. This can be done by calculating a sign exposure rate. in a shopping center by calculating the number of people who passed by a point of sale.

The second platform II comprises a first plan management stage 1 3 and space resources, making it possible to interpret the data of the geolocated contact points, a stage 14 for exploring and displaying data, a stage 15 analysis tool which is intended to restore the indicators in the form of a visual representation, and a revenue management stage 16, constituted by an external tool that cooperates with the predictive engine 9 for the optimization of the prices of products or services for example by calculating an estimate of sales over a predetermined period.

Finally, as indicated above, the third platform III is a customer relationship management tool whose purpose is to launch marketing campaigns that are triggered from triggering criteria that can be behavioral and / or geolocated.

It may be, for example, to launch marketing campaigns to any male individual who crosses a predetermined area before a predefined time.

This platform III allows the management of contact sheets relating to customers or prospects, these contacts can for example be business contacts (B to B) or consumers (B to C).

It is thus equipped with tools capable of communicating with the customers, in particular not sending electronic messages, of type emails or SMS to the customers.

As noted above, the medium used to deliver a proposal is chosen to be most relevant depending on the context.

The third platform III comprises a module 17 for triggering business processes from predefined parameters or particularly contextual and / or geolocalized information obtained from the data collection points or from the data coming from the outside. An exemplary implementation of the system that has just been described will now be described with reference to FIG.

In a first step 18, data from the physical contact points and data from digital systems of the connected place ecosystem are collected. In this first step 18, the data input and output stages 2 and 3 as well as the cache memory 5 and the relational database 7 are activated.

These data collected in parallel are combined (step 20) to be stored in the storage stage 4 (step 21).

In the step 20 of combining the data, the communication stage 3, the big data base 6 and the analysis module 10 are solicited.

Step 21 implements the base 6.

As indicated above, data from the outside is also recovered (step 22).

These various data are stored in the data storage layer 4, in particular but not exclusively in the form of geolocalised data, that is to say by considering the coordinates of the contact points from which they are recovered.

In the next step 23, the predictive engine 9 can be implemented to carry out a prediction of user behavior over the water.

The calculation stages 10, 11 and 12 are then implemented (step 24) to calculate business indicators as well as triggering parameters (step 25).

In the next step 26, the third platform III is implemented to trigger campaigns including but not exclusively contextual and / or geolocated.

In the implementation mode illustrated in FIG. 4, in which steps identical to those described above are designated by the same reference numerals, it can be seen that step 25 is an optional step, the calculation stages 10, 11 and 12 being able directly provide the data collected and analyzed to the third platform III.

In addition, the stored data may be provided to the business analysis stage (step 27) for viewing the data.

Finally, with reference to FIG. 5, there is shown an exemplary implementation of the system and the management method according to the invention which have just been described.

In Figure 5, it is to recover data from customers present in a stadium.

In particular, it is to locate spectators in real time according to a specific segment (products / client / behavior).

In the present case, it is a matter of obtaining information concerning types of visitors in order to obtain information on the location of certain categories, such as subscribers, families, and young people, by providing a geographical report. to present this information.

FIGS. 6a to 6f show another example of implementation of the system and method that have just been described.

The mode of implementation illustrated in these figures corresponds to use in a shopping center.

Figure 6a corresponds to a visualization of geo wifi terminals located in the shopping center and shows the traffic data communication with these terminals.

Figure 6b is a representation of the mall from tags connected for example bluetooth.

In the mode of implementation envisaged, the course of a user can be identified and followed (Figure 6c). It is also possible to monitor the daily activity of the shopping mall (6d), the specific daily activity of each store (Figure 6e), or the retail trade center's display rate (Figure 6f). Note also that the description of the invention which has just been made relates to an embodiment in which the system 1 collects, organizes and analyzes data from customers who are present or circulate in a connected space by recovering data. data from contact points.

The invention also relates to a management system capable of managing the relationships with clients outside the connected space, through the collection of data external to the connected space. The touchpoints may further be able to recover data outside this space.

Reference will now be made to FIGS. 7 and 8 which illustrate another embodiment of a system and method for managing the relationship with customers according to the invention.

In these figures, identical elements, and in particular the platforms as well as the various components of these platforms, are designated by the same reference numerals.

Figure 7 shows the Data Collection Platform I, the Performance Indicator Development and Reporting Platform II for data exploitation and visualization, and the Relationship Management Platform III. with customers who also provides space management and communication.

As can be seen, the system also comprises a platform IV for configuring the tools of the platforms I and II. This platform is also intended to configure a portal for accessing the system.

With regard to the platform I, it comprises, as in the embodiment described above, stages 2 and 3 of input and output of data and a layer 4 of data storage comprising a cache memory 5 , a big data base 6 and a relational database 7.

The database 7 is however modified, in this embodiment, in that it constitutes a relational database constituting structured repositories.

The calculation stage 8 also comprises a predictive motor 9, a big data analysis engine 10, a calculation module 1 1 and a module 12 for calculating triggers for communication, commercial and marketing actions.

In this embodiment, the calculation module 1 1 comprises two stages 1 1 'and 1 1 "constituting one of a geometric and geographical data calculation engine, making it possible to load specific algorithms related to the geographical and geometric data of the places. concerned and the other a search engine and calculation indicators to load specific algorithms related to the sector and the trade concerned, and also to view the data stored in the layer 4 storage.

As for the platform II, as in the embodiment described above, there is a stage 14 for exploring and displaying data, an analysis stage 15 for rendering plan indicators and a management stage 16. of income.

With regard to platform III, which is intended for the management of spaces, the relationship with customers and communication, it includes a floor 13 for managing plans and resources in spaces and a module 17 business process trigger.

Furthermore, the platform I further comprises a data processing and supervision module 28, which allows a first processing of the data made during the collection and during the exhibition and allows the supervision of the smooth running of the collection processes. and exposure.

The calculation stage 8 further comprises a motor 29 for providing materialized views, for the construction of a set of structured data corresponding to views and which are extracted from the big data base, a recommendation engine 30 which enables to provide the customer with the right content, the right product, the right service, at the right time, in the right place and on the right channel, a data sharing rules engine 3 1 that governs data sharing rights between various clients, and an authentication engine 32 for authenticating, creating and modifying unique identifiers, on different channels. Finally, the platform IV comprises a module 33 for configuring the access portal to the tools presented by the platforms II and III, a module 34 for configuring algorithms for configuring the algorithms loaded in the stage 8 of calculation and a stage 35 configuration of the fields, data processing rules for configuring the principles of collection, exposure and data processing performed by the input and output stages 2 and 3 and the module 28 for processing and processing. data supervision.

With reference to FIG. 8, during the implementation of this embodiment, step 18 of data collection is implemented by means of stages 2, 3 and 28 as well as modules 5, 7, 32 and 35, and the step 20 of combining the data by means of the modules 3, 28, 29, 10, 34 and 35 and the stage 4.

These data are then stored in the storage stage 4 and business indicators are calculated (step 24) by implementing the modules 29, 10, 34, 11 'and 11 ".

As in the embodiment described above, the predictive engine 9 as well as the recommendation engine 30 and the algorithm configuration module 34 can be implemented (step 23). Data from outside can also be retrieved (step 22) by implementing modules 2, 28 and 35.

In the next step 25, the triggering parameters are calculated by implementing the modules 12 and 34 and then implementing the third platform III to trigger campaigns including but not exclusively contextual and / or geolocated.

In the next step 26, the segmentation, targeting, and routing GRC capabilities (of platform III) use the exposure module 3, the processing and supervision module 28, and the management module 17. Triggering process and configuration modules for portal 33 and field configuration, data processing rules 35.

As described above with reference to FIG. 4, the data collected and stored during step 21 can be provided to the data exploration and display module 14, to the module 15 for rendering indicators on plans and to the module 1 6 for revenue management for their visualization (step 27), from an access portal described in module 33. In addition, step 27 may use modules 3 and 28 to expose the data for exploitation and visualization by third party systems, depending on the configuration and rules defined in module 35.

The system described with reference to FIG. 7, furthermore allows integration of data of planes provided by the stage 13 (step 37).

Furthermore, the communication module 3, the processing and supervision module 28 as well as the engine 31 and the modules 34 and 35 can be implemented to share enriched data with the big data base 6 (step 38).

Claims

A relationship management system with customers present in a connected space or outside of said connected space, comprising a set of contact points able to collect information relating to customers located in or outside information collection areas. collection areas, (PI, ... Pn) and potentially geolocated in space, a platform for synchronous or asynchronous collection of this data, means (4) for storing and organizing information, means (9 , 10, 11, 12) for analyzing and displaying the data stored in the storage means and means (III) for using the analyzed data for the execution of certain actions.

2. System according to claim 1, wherein the analysis means (10, 11, 12) comprises indicator calculation means, at least a part of which is intended to trigger predetermined actions, from the collected data.

3. System according to one of claims 1 and 2, further comprising means for entering data (PE) external to the connected space, the means (III) for using the data and the analysis means. being adapted to jointly use and analyze the external data for the execution of said actions.

4. System according to any one of claims 1 to 3, wherein the analysis means comprises a predictive module (9) capable of predicting a behavior of the customers.

5. System according to any one of claims 1 to 4, wherein the analysis means comprise means for correction and recovery of the stored data.

6. System according to any one of claims 1 to 5, comprising means for calculating a representation of the connected space.

7. System according to any one of claims 1 to 6, comprising means for the transmission of messages to client users.

8. System according to any one of claims 1 to 7, comprising means (10, 1 1, 12) for calculating trigger parameters for predetermined actions, said parameters comprising at least one parameter selected from behavioral parameters and / or or geolocated, information collected from the contact points, information outside the connected space, and / or information related to the uses of the services offered to the customers.

9. System according to any one of claims 1 to 8, wherein the storage and organization means comprise a memory (6) for storing big data, means (7) for relational data storage and a cache memory ( 5).

A method of managing relationships with customers in a space connected to or outside of said connected space comprising a set of contact points for certain geo - located in the space, wherein:

- information relating to customers located in or outside of the data collection areas is collected;

- Organize and store localized information;

- the stored data is analyzed; and

- the analyzed data are used for the execution of specific actions.

1 1. The method of claim 10, wherein the actions are determined from behavioral and / or geo-localized data.