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Digital Retail Intelligence

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by

Chris Paraskiv

on 15 July 2014

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Transcript of Digital Retail Intelligence

Foresight
Insight
SCALABILITY
Primary Objectives
Digital Retail Intelligence
Concept
Collect
Match and
Cross Correlate
Rules,
Qualification, Quantification
Actions
Actions are the specific call to action that has been issued and the direct result of that call to action i.e. accept offer, promote offer to friends via Facebook, purchase now, click on link, log-in to loyalty app etc.
The result action then can trigger an event with additional attributes based on the pre-defined rules.
All actions are logged and action attributes feed the predicative analytics model
Monitoring,
Alarm,
Alerts
Loyalty Programs
Results
Results maybe derived directly from the actions or are fed via third-party sources such as POS or CRM systems
The results module is used to determine exactly what the result of the action is (no action, purchase with value level, products or offer options transacted)
It is primarily designed to correlate the economic outcome to the prior processes
Reports
BI
Provide Retailers with Actionable Analitics
Deliver automated expert retailing and customer engagement systems that align with business objectives
Create disruptive solutions that become the must have digital retailing toolset
Architecture
feedback
Message Broker
Blix/GSM
Touch
Web/Apps
CMS
Message Broker
CRM
Loyalty Program
Predictive
Analytics
M2M
UI
Message Broker
Big Data
Server Cluster
Supplier
Consumer
Import data in real time where possible via API's from all relevant sources
Collect relevant matching data
MAC addresses
location
time
actions
requests
preferences
activity history
Utilise Master Data Management (MDM) capabilities to match dataset and relationships between objects and entities
Enable visualisation of relationships (devices, people, customers, actions, locations, retailers, etc)
All new data matched to existing known entities and objects in realtime
Enable intelligent queries of related objects and attributes
Feeds analytics and predictive analytics engine
Define rulesets under “if this then that” structure
Rules look for patterns of matches and relationships that then trigger specific actions/events or grouping of objects (target customers)
Rules trigger events or look for specific event attributes and events trigger rules to be actioned
Rules can be simple of highly compound clusters of rules. (If a prospect is in a location and a time of day, has provided consent and has specific attributes and has accepted similar offer previously, then offer a proposition with the following attributes….)
Rules are refined over time based on event outcomes to create more precise and relevant offers with higher transactional yield and profitability via Predictive Modelling
Based on historical data, creates a statistically accurate predictive model of behaviour
Model is exported into a PPLM XML structure and becomes an executable ruleset with prescribed event outcomes
Ongoing result input continually creates a more statistically accurate models. This becomes the core IP of the system.
Offers
Offers are either personal or public offers based on an event. The event maybe time of day, surplus of product or a person matches specific attributes
The offer maybe presented to the person(s) in a number of methods. Email, in-app message, digital signage, SMS etc when actioned.
The offer content is managed within a CMS with the variables managed by the Offer module (specific discount, price point, timeframe etc)
Each offer is has an audit trail to determine what was offered, based on what rules and specific attributes. This enables it to be analysed and used for predictive modelling.
Offers can be varied to determine what specific offers provide the best yield under different conditions
Event
Rules trigger events or look for speciffic event attributes and events trigger rules to be actioned
Rules can be simple or highly compound clusters of rules. (If a prospect is in a location and a time of day, has provided consent and has speciffic attributes and has accepted similar offer previously, then offer a proposition with the following attributes….)
Events trigger offers with speciffic attributes to one or multiple parties.
Events are actions or a collection of actions that are triggered by rules or have occurred and have been reported by an external systems (i.e. a purchase or app download)
When an event occurs it can trigger a rule or be sent to a message broker to update or inform a third party system.
This function orchestrates all system messages between components and external systems and sources
Each component is either a publisher or subscriber (or both) to specific sources or events
Event Broker interrogates the data and decides which competent requires what, in which format or structure
Staging
Collection of Independent Data
Message Broker
translate
normalize
Past
Present
Future
Historical data
BI
Data Warehousing
Data Mining
Spontaneous actions to live stimuli
Visualization
Location Intelligence
Context Intelligence (CRM, Loyalty)
Big Data Analytics (MapReduce)
Data Driven Decision Management
Longitudinal Studies
Predictive Modelling
Inductive Reasoning
Statistics
Causal
R
Predictive Analytics
Full transcript