Archive for October 2013

How to Deliver Omnichannel Real Time Decisions

Omnichannel execution has become imperative for retailers as consumers increasingly combine their shopping activity across online, brick & mortar and mobile channels.

With omnichannel, when a customer engages in any channel, the retailer is aware of their prior interactions in other channels and uses that knowledge to optimize the interaction in the current channel.

A well executed omnichannel strategy requires real time decision capabilities - the ability to process events as they occur, combine the event with other valuable data, gain intelligence from the data and decide on an action to improve the customer interaction.  All of this done in real time.

Real Time Decision Process


Entrigna Blog - Omnichannel Strategy - Real Time Decisions Process

Real time decisions process

A Real Time Decision Process can be viewed as five distinct steps.


Execution of omnichannel real time decisions is triggered by an event.  An event can be any number of things but is usually initiated by a customer action; examples include,

  • Customer visits website
  • Customer uses mobile app
  • Customer visits store
  • Customer calls contact center
  • Retailer geo-locates customer.

The event presents an opportunity to engage and must be captured in order to initiate the real time decision process.

Virtualized Data

Sometimes, knowledge of the event is sufficient information to take action.  More often, additional data must be leveraged to improve intelligence.  Many different types of information is potentially needed including

  • Customer profile
  • Transaction/sales history
  • Channel interaction history
  • Social activity history
  • External data like weather, traffic, national/local events.

Data virtualization is the technical process that integrates these disparate data sources in real time into a usable format.


Intelligence must be derived based on the event and virtualized data to determine the optimal action.  Predictive analytic capabilities are necessary and a wide range of decision frameworks must be available, including

  • Rules engine
  • Complex event processing
  • Classification / clustering
  • Optimization
  • Machine learning
  • Artificial intelligence.

The breadth of decision frameworks is necessary because different business objectives require different analytical approaches.  For example, a rules engine works great when recognizing a customer for a milestone.  Likewise, event processing is well suited for identifying potential customer dis-service scenarios.  Finally, optimization techniques work well when making decisions about which promotions to place in front of the customer.


Once determined, the decision must be integrated with a customer facing channel or business process in order to impact the outcome in real time.  The types of actions should be related to achieving core objectives such as

  • Offer optimization
  • Winning/completing the sale
  • Customer lifecycle milestones
  • Customer service (cross channel coordination, surprise & delight, recovery).

Feedback takes two forms.  First, the outcome of the action/decision is fed back to the algorithms used in the Intelligence step.  This can be done in real time for online learning algorithms or stored and leveraged in a batch mode for off line learning algorithms.

Second, data and insight from the Real Time Decision Process is fed into enterprise data management processes like customer relationship management (CRM) and customer data management (CDM).

It's important to note that real time decisions are related but separate to enterprise data management processes in which both rely on each other as inputs to one another.  As a consequence, implementation of real time decisions does not require a multi-year, multi-million dollar enterprise data management project to be complete.

Execution of real time decisions is a complex set of capabilities that include predictive analytics, data virtualization and real time decision software.  However, when done well, real time decisions delivers the full promise of omnichannel benefits.

What do you think?  We'd love to hear your thoughts.

Importance of Real Time Decisions in Omnichannel Marketing

With the growing trend of consumers combining their shopping activity across online, brick & mortar and mobile channels, significant discussion has arisen in the retail industry about the need for omnichannel marketing.

What is Omnichannel

While perhaps a single definition doesn't yet exist, one way of thinking about omnichannel marketing is that it is centered around the customer.  Historically, multi-channel strategies have tried to ensure brand consistency across channels and optimize performance in each channel based on respective strengths.  Multi-channel is more of an inward focused approach.

With omnichannel, when a customer engages in a particular channel, their prior interactions in other channels is known and that knowledge is used to optimize the interaction in the current channel.  Omnichannel is a more of a customer focused approach that works alongside the customer as they interact with the retailer.

Taking this one step further, omnichannel should also leverage knowledge of one other huge "channel" - what's going on in the outside world.  This includes information like location, weather, traffic and national / local events which can have as much impact on optimizing the customer interaction as anything else.

Entrigna Blog - Omnichannel Strategy & Marketing

High level concept of omnichannel

Omnichannel Execution

In order to create maximum value, omnichannel strategies must be directly applied to improving performance of core business objectives.  Otherwise, retailers run the risk of implementing a very complex initiative without an end goal in sight. For the marketer, a well executed omnichannel strategy can improve

  • Offer optimization
  • Conversions / transactions of sales leads
  • Customer lifecycle management - recognition of events & milestones
  • Customer service - cross channel coordination, surprise & delight tactics, recovery.

Omnichannel implementation requires many capabilities including enterprise data management solutions, predictive analytics and real time decision software.  It may also require changes to organizational design and operational processes.

Role of Real Time Decisions in Omnichannel

Real time decisions is critical for a well executed omnichannel strategy.  Omnichannel leverages knowledge of prior interactions across channels to optimize the interaction in the current channel.  In most cases, the opportunity for the retailer to interact with the customer in the current channel is "now" or real time.

Execution of omnichannel and real time decisions is triggered by an event.  An event can be any number of things but is usually initiated by a customer action; examples include

  • Customer visits website
  • Customer visits brick & mortar store
  • Customer engages in a social channel
  • Retailer determines geo-location of customer.

A retailer must be able to capture this event and leverage additional data like prior interactions across channels in order to derive intelligence.  A wide range of tools from sophisticated predictive analytics like machine learning algorithms to more straight forward business rules engines should be leveraged to derive intelligence.  From this intelligence, a decision is determined for the optimal action.  The decision must be integrated into a customer facing channel or business process in order to impact the outcome in real time.

The entire process, outlined above, is called real time decisions.   As you can see, it is central to enabling the knowledge and coordination of actions across channels.  In the next post, we'll talk more about the execution of omnichannel real time decisions.

In the meantime, what do you think?  We'd love to hear your thoughts.