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Analytics-as-a-Service: Turning data into profits for MVNOs

After large-scale research, McKinsey identified five key areas that set up MVNOs for success, and out of those five, four of them depend on data from Analytics-as-a-Service.

In this article, we’ll dive into those elements and explain how Analytics-as-a-Service turns data into profits for MVNOs.

McKinsey’s 5 elements of MVNO success

The five elements for MVNO success that McKinsey identified, are:

  1. Unique brand positioning and value proposition
  2. Joining forces with MNOs
  3. Build marketing strategies around the needs of their target audience
  4. Focus on customer satisfaction and sales
  5. Concentrate on operational efficiency

As mentioned, out of these five elements, four require insights from Analytics-as-a-Service, aka data, which provides the information needed to pinpoint services that should be developed or optimized, as well as the type of customer you should target, and which drives the MVNOs marketing strategy. We’ll now discuss each of the four elements MVNOs depend on for profitability, and how Analytics-as-a-Service ties in:


#1: Unique brand positioning and value proposition

For an MVNO brand to have value, it must mean something to the customer and to achieve that aspect, it needs to be exclusive.

Successful MVNOs focus on developing a unique brand positioning by targeting specific groups of people, such as certain communities, age groups or geographical locations. For example, Safaricom via M-Pesa, dominates the Mobile Money arena in Kenya.

Targeting specific groups requires data in order to identify markets that don’t fit into traditional marketing practices, or would be too expensive, using the same business model that every other MVNO uses.

Once data via Analytics-as-a-Service is obtained, the MVNO can create segment-specific pricing together with distribution strategies like POS, gas stations and so on.

No matter their level of maturity, MVNOs must find ways to differentiate themselves from competitors in very specific customer segments.

In addition, MVNOs must strive to continually add innovative products and service bundles to their offerings. Consumers today don’t just want a low price-point; they want the convenience to satisfy all their needs.

Analytics as a Service: Turning data into profits for MVNOs

#2: Build marketing strategies around the needs of the target audience

There are three primary reasons MVNOs have not yet matured in developing optimized marketing strategies which impact the bottom line:

  1. They fail to maximize the use of data, aka Analytics-as-a-Service, which provides information around their target audience and which needs to drive the marketing process.
  2. Marketers in the company do not understand the end to end product and how much it costs, as well as how it came about, what element costs a lot, which ones cost a little, which add value and which don’t. Therefore, they cannot build meaningful and optimized marketing strategies.
  3. Lack of understanding around the industry and its trends. Again, this insight comes from the data. Analytics-as-a-Service not only provides the organization with the deep insights it needs to grow marketing initiatives but also offers competitor information to ensure the business stays on top of latest trends and developments.

In general, MVNOs simply use call records and billing information from the MNO for insights around how their products are being used. But this is only a small part of the picture. Analytics-as-a-Service allows MVNOs to take away the abstraction of messy data management and complex predictive modelling and takes decision making to a new level.

With the rich data that Analytics-as-a-Service provides, advanced analytics helps the business identify trends for specific types of customer segments. For instance:

  • Who are the mobile gamers and what are their needs?
  • Who are the telecommuters, and what are they looking for?

This kind of data shows a more complete picture that MVNOs can use for better decision making, optimizing their network, and to develop services and marketing campaigns targeted at specific audiences.

customer satisfaction

#3: Focus on customer satisfaction and sales

The best MVNO players painstakingly manage multi-channel distribution strategies in order to formulate a targeted go-to-market strategy.

To allow for this, they need to ask questions around these seven points:

  1. What is the best network channel mix currently and in the future?
  2. Do incentives work for different channel participants, while also making sure payout to channel partners takes place?
  3. How does the MVNO ensure high customer satisfaction and create processes that are not easily duplicated by competitors?
  4. How can the MVNO effectively cross and upsell products through its online presence?
  5. What are the implications of the channel strategy on the business?
  6. How to develop customer satisfaction processes that are effective feedback drivers and build loyalty?
  7. How do third parties impact the service experience and what issues do customers have around the touch points?

#4: Concentrate on operational efficiency

Successful MVNOs reduce costs by joining forces with the right mobile virtual network partners which take customer experience seriously, and who make it easier to grow without huge upfront costs.  

MVNOs need to decide which services to keep in-house and which to outsource, keep tight control over variable costs, and make sure fixed costs to are at a minimum.

Adapt IT Telecoms offers end-end Analytics-as-a-Service; some areas which are covered in the solution include:

  • Automated carrier cost optimisation
  • MNO Invoice reconciliation
  • Customer segment analysis
  • Real-time alerts based on configured events e.g.
    • excessively high usage
    • changes in certain customer behaviour patterns
    • thresholds over a route
  • Detail product, subscription and VAS usage and spend analysis
  • Interconnect and roaming analysis
  • Customized KPI and executive dashboards
  • Subscriber growth and trend analysis
  • Inactivity and churn watch models
  • Device analysis
  • In-depth analysis of all network event records including all traffic types and technologies (Voice, data, text, WiFi, VOIP or any other available source) in one central source

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