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New rules of customer engagement: The game of personalization

Author: Flytxt Dataeconomicvalue
by Flytxt Dataeconomicvalue
Posted: Nov 30, 2018

Digital engagement is the talk of the town. Remarketing, online-to-offline and offline-to-online engagement, switching, and omni-channel engagement paradigms are here to stay. With the increasing adoption of digital channels by customers and enterprises, they have now become an integral part of customer engagement models.

How is Customer Value Management adapting to the digital world? After all, Customer Value Management (CVM) in its traditional sense is engaging customers with the right offer and the right time over the right channel, i.e. contextual engagement.

To delve deeper into the dynamics of CVM, omni-channel engagement, and traditional Next Best Action / Next Best Offer (NBA / NBO) models, we need to understand the primary parameters of a targeted engagement model, i.e. where engagement dynamics are informed by a specific goal (in the case of CVM, the goal is Customer Lifetime Value or CLTV).

The three dimensions, which act as constraints in any targeted engagement model, are:

Revenue / other organizational goals:

This is the primary constraint in engagement. No engagement model can completely ignore its primary aim, i.e. – maximizing the value of each customer interaction.

Customer needs

At the same time, an engagement paradigm also needs to consider what the customer wants / needs at any moment of time.

Resource

In most engagement paradigms, the resource constraint comes in terms of cost of communication, often called channel costs.

Traditional engagement models

Open Market / ATL Communications have resource as their primary constraint, as these are costly. In such expensive channels, the focus lies more on maximizing revenue rather than meeting customer needs. Additionally, it is difficult to adequately meet customer needs without a segmented communication channel.

In traditional CVM models of engagement, the resource cost constraints could be mitigated using telecom operator’s own channels (traditional channels like USSD / IVR / SMS, etc.). These models try to match revenue / other organizational goals with customer needs. Contextual communication paradigms and triggered programs helped serve the right offer at the right time to the right customer, however, communication channel constraints have a very little impact on the design.

In the traditional Next Best Action / Next Best Offer (NBA / NBO) engagement model, revenue and similar considerations take a backseat, as the primary model is to engage customers at a relatively lower impression level, i.e. ensuring customer needs are met keeping resource utilization at their lowest. Although it cannot entirely be ignored here, revenue is not the biggest priority here.

Losing control: Moving to a digital world

With the engagement moving from legacy to open channels (e.g. email) or traditional digital channels (e.g. own website) or even social media, organizations need to adopt their engagement models to suit this new reality. This shift may further cause organizations to lose their fine-grained control and be at the mercy of the new, smart channels.

Are you using email to communicate? Email programs will suppress delivery notifications so that you don’t get any acknowledgment of who read your missive. Are you using your own website? Real- time engagement takes a backseat and messages are cached. Moving to social networks, customer-level response tracking simply doesn’t work anymore.

In this environment, losing even one of the three dimensions of engagement can be disastrous. Let’s take an example. Enterprise A tries to connect with their customers on Facebook. Simultaneously, there are 15 different enterprises, some of them direct competitors to Enterprise A, vying for the same customer, In this scenario, Facebook shall only show Enterprise A’s communication to the customer if and only if their budget is adequate.

About the Author

What does a typical customer purchase journey look like? A customer sees your product, buys it then may repeat the purchase if they are satisfied with the outcome.

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Author: Flytxt Dataeconomicvalue

Flytxt Dataeconomicvalue

Member since: Nov 26, 2018
Published articles: 4

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