Customer Experience for Nomadic Users

Nomadic behavior fundamentally changes the experience expected by consumer and enterprise customers.  It is a key value factor for both new and existing operators.

Nomadic Broadband Customer Experience

There is a a rapidly growing class of data user – let’s call them the digital nomads.  They are always connected and have high connectivity expectations.  Nomadism isn’t a demographic characteristic confined to an age group, profession or gender.  It’s a behaviour that involves heavy engagement with data using one or more portable devices, but not mobile “on the go”.  In fact, nomadism is about sitting down and concentrating, not just casually clicking. Nomadic users are not “broadband users” or “mobile users” — they are just data users above all else. That’s a new way of thinking for many service providers.

Just as the “mobile behaviour” went from unusual to normal in the first decade of the century, so “nomadic” behaviour will become the norm for most people.  For sure, one important consideration is the adoption curve for this “new” behavior and clearly we are already well along that curve.  More importantly it is a shorter curve than was the case for mobile: if we take tablet sales and installed base as a proxy, we have a global compound annual growth rate of 40-50% through 2016.  Care is needed to differentiate between growth in the behaviour, and growth in its impact on consumer buying decisions (which is a function of competition). 

Given that context, there are three main factors that determine the impact of nomadic customer experience on future cash flows:

  1. Adoption Curve of nomadic behaviour for a particular market and geography.
  2. Competitive Environment, and in particular the class of competitor(s) – greenfield, cable, mobile telco, integrated telco, metro-only, public – since each class of competitor brings a different set of strengthes and weaknesses based on their own technology and operational legacy (or lack thereof).
  3. Operational Readiness.  What is the execution gap that needs to be closed to deliver the targeted experience – how long will the required transformation take?  At a simple level we can split this into the areas discussed above – seamless connectivity, nomadic bundles and customer relationship management.  But if we take a common industry model of the underlying systems involved there are some forty different technology capabilities that need to come together to achieve those outcomes.

In practice, a common framework can be used for assessment of operational readiness across both the operator in question and its competition.  By assessing capability maturity systematically for each of the main areas of the target experience we can understand how the evolution over time of competitiveness in the different parts of the experience.

That’s only helpful if we also understand which parts of the experience have what impact on consumer buying decisions, and hence lifetime value and future cashflows.  That needs to be understood by segment and per market.  Now we have a problem – the “pure” model that this analysis implies is too compex to be practical and actionable:  It’s not useful to be assessing the impact of forty different capability areas on multiple journeys through multiple touchpoints for multiple target segments. We actually need to determine a relatively short list of capability areas that have significant impact on competitiveness for the most important touchpoints for major segments.  This can be achieved using global data so that the excercise does not have to be repeated on a per market basis.

In summary then, the following steps apply to determing impact of customer experience related to any new behaviour, but we’ll take nomadicity as the example:

  1. Identify major target segments (preferably 4, no more than 6) and key competitors.
  2. Build the simplified capability impact model – key capabilities to deliver the most important differentiators for those major segments.  In the case of nomadicity this typically means the capabilities to deliver “seamless connectivity”, “nomadic bundles” and “one relationship”.
  3. Model the adoption curves for each of the major segments.
  4. Using the simplified capability model to determine expected operational readiness and competitor readiness for each key differentiating capability.
  5. If necessary, conduct additional primary research to validate for the market in question the impact of the key differentiating capabilities on buying or switching decisions.
  6. Combine the adoption curves with the competitive capability and decision research to model impact on future cashflows.
  7. Conduct scenario analysis to determine which investment programs have the most significant impact on future cashflows. 
  8. If the analysis is for the benefit of management, the next step is to prioritize investment programs accordingly.  If the analysis is passive, for the purposes of valuation then it is necessary to factor in the current course and speed and the propensity of the exisitng or proprosed management team to drive postive change.

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