CVM vs CEM – should they be aligned?

I recently started looking into Customer Value Management (CVM) and how it relates to CEM.  In my mind there was less clarity on how these two disciplines interact with each other and how that interaction can be made better?  After all, I still remember a quote from Mr Jagbir Singh, former group CTO of Airtel – “I am not doing CEM for charity.  It has to make money for me”.

Let’s first understand the differences between CEM and CVM –


  1.  Objective of CEM is to deliver consistent, superior experience at all interactions in order to build customer loyalty and eventually lifetime value.  Objective of CVM is to improve profitability by targeted offerings at different interactions. So CEM is one of the enablers of CVM.
  2. Customer profitability is key metric for CVM but customer retention is for CEM.  So CVM can provide key input to CEM in terms of differentiating customer experiences for different personas
  3. CVM requires understanding customer value drivers, migration patterns while CEM needs deep understanding of empathy and expectations


Operators incurs customer acquisition costs for every new customer as well as every customer renewal.  Over a period of time, total revenue that a customer generates exceeds initial CAC as well as on-going maintenance costs of customer to generate positive contribution to business.  For prepay customers, CLV is moderate but their break-even period is smaller – typically between 7-9 months.  For postpay, CLV is higher but so is their break-even period – typically between 18-20 months.

If an operator delivers good customer experience through the consolidated use of data, analytics and subjective perceptions, it reduces the on-going maintenance costs of customers in terms of reduced calls to contact center and reduced time spent by back-end staff on resolving customer complaints.  With good customer experience, it is easier to upsell and cross-sell new products and services.  Data from various systems of CEM solution also enable to understand the customer behavior and interests that can be used for micro-targeted offers.  Thus good CE helps reduced break-even period and increase CLV.

But CVM also helps to bring business focus for delivering customer experience management.  Customer value based segmentation can show you which segments are your most valuable segments over a period of time.  CVM analysis also shows areas of cost improvement and where CEM efforts should be focused.  It also give important input into creating differentiated customer experience.  For example, proactive care can be prioritized for customer segments with CLV beyond certain business determined value while self care channels should be optimized for use by lower CLV customer segments.  Different CEM personas need different treatment and their net contribution to business is an important determinant for differentiating CEM.

Based on my experience, many operators have CEM initiatives but only a few have exhaustive CVM programs.  For operators that have both CEM and CVM programs, there seems to be chinese wall between the two and hence full potential of both programs is not realised.  I recommend strong linkage between both CEM and CVM initiatives so that CEM initiatives lead to increase CLV and different personas get relevant, differentiated customer experiences based on their value to the business.



Voice over WiFi – how to make it sticky through superior customer experience?

There is an intense pressure from OTT players on telecom operators, eating into their revenues. They turned operators into utility pipes but there is nothing brutal than eating their core voice revenues with Voice over OTT such as Skype.  According to Telegeography, skype voice minutes increased from 6bn to 55bn minutes  from 2005 to 2013, while international voice traffic decreased from 37bn to 35bn minutes in the past 8 years.  The difference of 20bn minutes amounts to at least $200m of lost revenue with conservative estimate.









In order to fight back, operators have started launching Voice over WiFi, which allows seamless calling over WiFi without having to use any OTT app.  This is a win-win situation as the customers get cheaper calls, especially when they travel internationally, but for CSPs when customers use WiFi indoors, reducing operator burden to improve costly indoor coverage and saving CAPEX and OPEX.  Of course, operators have to upgrade their packet core to IMS to enable VoWiFi calling.  But I think there is a clear business case of CAPEX and OPEX savings even after including the IMS upgrade costs.


However, VoWiFi is similar to best effort service as it goes over packet network.  It is similar to VoLTE already  launched by many operators.  But VoLTE delivers poor quality especially indoors due to high attenuation of LTE high frequency signals indoors.  But in order to encourage customers to use Voice over WiGi, and ensure they continue to use Voice over WiFi, operators have to ensure good voice quality over their WiFi as well as seamless handover experience between VoWifi and ViLTE.  It would involve monitoring S2a and S2b interfaces and creating a service model that can track voice Key quality indicators.  It also makes sense to take actual customer feedback on voice quality (similar to what Skype does when they ask you to rate call at the end of each call) and correlate that to KQIs to further tune.  If ePGW is made part of IMS core, probe costs can be saved, making a cost effective monitoring.  Per session voice capability monitoring is key to debug any voice quality experience issues and take corrective action.


:Lastly, it is important to communicate advantages of Voice over WiFi in simple terms to customers and encourage them to use it.  Instructions on Locating and enabling Wifi calling on handsets should be made available across all contact channels and customer service should be educated to inform the customer on any inbound call.


Many US operators have already enabled Voice of WiFi calling and it remains to be seen how much usage is shifted to voice over Wifi and how much CAPEX and OPEX it has saved to operators and most importantly, how is the customer experience.

Why there is a huge variation between EBITDA margins across operators? Not all the difference related to CSP performance

Recently, I was doing study of the operating margins of mobile operators from different regions of the world and one thing struck me – There is substantial difference between margins of Western European operators and South East Asian Operators.  SEA operators have margins on average 23% higher than those of WE operators (Figure 1).   So is the difference due to much efficient operations of SEA or there are some other factors involved.








Figure 1:  EBITDA Margins between WE and SEA Operators


I looked at the cost structure of mobile operators to try to understand the potential cause of difference using data that I have gathered from my experience working in the industry.










Figure 2: Mobile Operator Cost Structure


As you can see, the cost structure components are shown as % of revenue and these are average numbers calculated from the data of around 35 operators that I have.  There are few differences that can explain the differences in the margins –


a.  Customer mix – SEA operators have predominantly prey mix ranging from 80% to 95% while WE operators have postpaid customers dominating the mix racing from 60% – 80%. So SEA operators have strains away advantage of 15-20% margin as SAC and terminal subsidies are much lower in these markets.


b.  There is not huge difference between personnel cost as SEA operators have large low wage staff vs WE operators having small but expensive labor.  So the difference might be 2-3% points

These two points account for 17-23% of the difference in the margins and suddenly you can see that SEA operators’ higher margins are not necessarily only due to their efficient network and IT operations.  But there are some clever operators such as Airtel who have used pay per use model for network and IT usage further reducing network and IT costs.  Outsourcing and network sharing has also helped SEA operators to optimise these network costs and enhance margins,


However, network sharing and outsourcing has it own challenges and agency costs that have reduced the original optimistic savings that operators had expected.

So important lesson here – when you compare operators, be careful to compare apples to apples to understand the drivers of difference in performance.


How can Mobile Network Operators (MNOs) complement Unique Identification authority mechanism of Govt of India

Recently, I have been thinking hard to develop new use cases to exploit and monetise operator data.  I have to admit that there are not many use cases where data can be successfully monetised due to variety of reasons – partial data in silos, need for cooperation with other operators for economies of scale, privacy regulations and lack of credible business models.


In India, Govt has successfully rolled out largest identity authentication program in the world calls AADHAR by which a person’s identify attributes including biometric data are captured and securely stored for variety of uses including consumption of Govt services and subsidies.  MNOs also store many of the attributes that AADHAR system captures such as name, address, mobile number as well as photo except biometric data.  AADHAR uses two step authentication to confirm person’s identity – put AADHAR card and then also enter OTP password sent to registered mobile to authenticate your identity.  This mechanism though better than usual username and password has potential issues that fraudsters can exploit:

  • Mobile number given at the time of AADHAR registration is not validated to confirm that it belongs to you
  • Unless mechanisms are developed to check biometric data through mobile, if fraudster stores AADHAR card and mobile, he can misuse the identity before mobile is blocked.


When MSISDN is registered as part of AADHAR process, name, address can be validated against MNO database so that repeated paperwork regarding name and address proof can be avoided, improving efficiency of the process.   MNOs have historical as well as up-to-date data regarding MSISDN such as location, stolen or not, roaming or not.  I feel this data can be used to add another layer of authentication to complement the existing 2-step mechanism.  For example, 2-step OTP process can be disabled if MNO has the IMEI status as “Stolen” in its database.  Additional SIM based security mechanism where mPIN similar to bank’s IPIN is used to further improve authentication mechanism can be considered.  mPIN is similar to private PIN that is never transmitted over the air.


In this process, explicit consent from the customer should be obtained and this consent should be used only for the authentication purpose and nothing else.  This consent should be obtained every single time.


Such a trial was successfully carried out in the UK as part of Open Identify exchange program. I feed that this is a clear opportunity to monetise customer data that MNOs hold.  Identity theft cost every Indian Rs 7500 or $120 as per study by Microsoft.  So there is huge benefit in exploring MNO data to complement AADHAR mechanism and make it foolproof so that Govt services can be availed by those to whom they are meant for!


Customer experience Management for Fixed Broadband

For the past couple of years, all customer experience management solutions focused mainly on the mobile network service providers for obvious reasons – Mobile is growth area, there is much more competition in Mobile than fixed and there are many more issues related to mobile service quality due to inherent Radio and mobility issues vs fixed with no mobility.

However, fixed operators are becoming interested in Customer experience for couple of reasons –

a.  Most fixed operators are incumbents and also have mobile operations .  They have done Fixed-mobile bundling to defend against disruptive players.  However, this is not a long-term solution to retain customers ^ capture value.   So these operators want to assess CE for both fixed and mobile operators

b.  Many fixed operators are facing increasing competition as local loop is getting unbundled

c.  Most of the customer care for fixed broadband is reactive and hence not CE enhancing.  Customers are increasingly vocal about broadband access issues and expect proactive care through digital channels

Fixed operators, not used to delivering great customer experience due to their protected incumbent position till now, are demanding CEM solutions that are same as the CEM solutions that are deployed for mobile networks.  However, such demands are ill thought as there are some inherent differences between fixed and mobile network.

a.  There is no mobility in fixed network unlike mobile and many of the quality related issues due to mobility are absent in fixed network

b.  Fixed access have different flavours – xDSL, FTTX, Cable vs mobile who has similar network across different generations

c.  Tapping points at access are much more numerous along with 10X data volumes.  So probe based CEM solution are not cost-effective for fixed.


Majority of the issues faced by fixed operators are related to accessibility and availability of broadband services.  Also, there is no burning requirement to track every OTT application per household in fixed.  Majority of the issues in fixed broadband accessibility are related to in-home WiFi issues and hence visibility of WiFi is critical in diagnosing and resolving issues.  One APAC operator mentioned 40% of the complaints are related to accessibility and 80% of these 40% are related to in-home issues – router, WiFi, etc.


So a different approach to service and customer experience management should be taken to create cost-effective CEM solution for fixed broadband provider.   Data from TR69 compliant modems can be looked into deriving CEM quality level insights.  This is especially useful when provider doesn’t own local loop equipment and is operating through a wholesale service provider.


Going forward, I think there is increasing traction among fixed broadband providers to look into solutions to manage and improve customer experience.


Customer Segmentation for contextual marketing in Telcos

CSPs have been using customer segmentation for many years now – demographic, usage based and ARPU driven.  In the times of voice and SMS, such segmentation sufficed the purpose of selling these basic services.  With data explosion and revenues increasingly influenced by data and VAS, such segmentation is not fit for purpose and needs to change.

In addition, CSPs have granular customer interaction data passing through their network – Apps used, URLs accessed, locations and times for access, type of network of access, recency and frequency of access and so on.  A lot of these contextual data is extremely valuable for segmenting customers in a different way – using their interests derived from these data.  Some CSPs have started exploiting these data for segmentation but there are challenges ahead in terms of technology, data privacy, derived interests and more importantly potential business benefit in terms of uplift over existing campaigns.  I would like to dwell on some of these aspects in this article.

1.  Technology Issues

Much of the traffic today on the mobile internet is transitioning to HTTPS.  With some estimates, more than 60% of traffic is HTTPS.  Customer conscious of their privacy, are increasingly using VPN services to access internet.  Much is the URL and APP data gathered by CSPs become not so useful when these connections are encrypted as CSPs lose the long URLs they used to get before encryption.  These long URLs allow them to derive customer’s intention and hence interest.

Second challenge is to classify multitudes of URLs and APPs into meaningful categories and interests that can then be used for further segmentation.  There are organisations such as similarweb and ZveloDB that offer classifications.  However, output of these classification engines is not of great quality because input are the high level URLs due to encryption and HTTPS issue discussed earlier.

So quality of category data presents the first challenge to segmentation.

2.  Cluster Dimensioning Issues

Each category/subcategory output from categorisation tool becomes a potential dimension and these can go up to as high as 300.  With recency and frequency values over 300 dimensions, the input becomes quite complex and cluster output quality can be poor.  So concepts from text analytics might have to be used to manage the dimensions and also preprocess data.  Concepts of TFIDF – Term Frequency Inverse Document Frequency can be applied to dimension matrix to remove rare or more frequent terms and then balance the remaining terms as per their frequency across all corpus.  Such processing is shown to to give much high quality cluster output.


3.  Creating Personas or segments from clusters to make sense of them

When you create clusters, sometimes it is difficult to describe these clusters to the business community.  Supervised classification using clusters can create rules that can help define clusters.  Another challenge is to integrate existing demographic, psychographic and value information with clusters to create personas – way to describe segment fully in terms of their characterisitics.  Since demographic and other information is available on sample basis, it is tricky to merge it with cluster information to create personas.  Additional market research for the customers in the sample for clustering might be needed to integrate this information.

4.  Data Privacy Issues

CSPs and OTT players are governed by different laws with respect to privacy.  For example in the US, FTC laws govern Facebook and Google while FCC laws governs CSPs.  FCC laws tend to be tougher on privacy than FTC and hence OTT players have some advantage of being able to use your data vs CSPs being able to use data for upsell and cross-sell or even making content free through ad-supported sites.  I think customer education with respect to privacy and what data CSPs can really see versus what Facebook and Google know about you might help CSPs to convince its customers to share consent.


5.  Return of Investment

We all talk about personalized offers generating huge benefits – Netflix, Amazon have proved it many times. But there is little evidence of CSPs achieving substantial lift through such behavioral segmentation over their existing baseline segmentation based on demographic and service usage.  The key challenge is the attribution where it is tricky to measure and attribute incremental value to such behavioral segmentation and not to other aspects of the business that are changing at the same time.  Sophisticated econometric modeling is needed to measure and quantify attribution.


Despite these challenges, there are huge opportunities for CSPs to make use of their data to create meaningful segments based on customers interests.  In addition, they have huge advantage in terms of customer context – device, location, time, network presence which can be critical for contextual marketing in addition to clustering.


I feel that in the coming months, we can see lot of action from CSPs on this front – Verizon with Yahoo, Telenor with Tapad, Telefonica with Amobee and so on.


Analytics in the Telco Context

Big data analytics has been hot topic for some time now and like everyone else, I thought I needed to understand it better from telco perspective and sieve through the hype to understand the reality myself.

So I proceeded to do analytics certification at Wharton Business School recently and their classification of analytics was pretty good.








If I see current Telco focus, it is in the top left half of this table – Customer and Operational Analytics in terms of their descriptive and predictive capabilities.  So I will focus on these two in my current post.

Telcos are doing a lot of descriptive analytics on the customer side – customer segmentation – demographic, psycho-graphic are main focus.  However, with the use of granular service level data per customer, some operators have started to look into lifestyle or interest based segmentation with RFM (Recency, Frequency, Monetory Value)  based clustering.  These lifestyle segments are richer than existing segmentation and will be used to enhance current customer profiling.  Technology is also enabling the use of cross-device behavior analysis – companies like Tapad are leaders in this field.

Predictive customer analytics is where Telcos are still scratching the surface.  At present, most are occupied with churn prediction but very few are dabbling in the area of machine learning and CART techniques to use lifestyle segments to predict propensity to accept targeted content offers.  Prescriptive analytics connects predictive analytics to maximisation of business benefits.   There is lot of scope for automation and machines learning in prescriptive analytics and telcos are way at the bottom of the learning curve.

The area of operational analytics is much less explored by telcos.  Today, very basic descriptive analytics on operations is carried out, mainly on the network operations side.  Some analytics is carried out on the customer care operations as well.  However, the real benefit in network operations is predictive analytics that can anticipate network and service problems before they occur so prescriptive analytics can applied.  For example, analyzing alarm data and performance management data  and using regression techniques to predict service quality degradation for future traffic growth can take proactive actions to fix before it happens, thus saving huge amount of firefighting efforts in the future and protect network quality brand.


In future, actions can be improved through machines learning, analysing impact of past actions on service quality and automatically recommending changes to future actions.  this area of prescriptive analytics will generate the biggest benefit for telecom operators.

However, as many believe or suggested, predictive and prescriptive analytics alone are not going to solve all problems of telcos.  Associated processes and Governance has to change to act upon the insights from analytics.


I am very excited about the use of predictive and prescriptive operational analytics and look forward learn many more interesting use cases.

Business to Business CEM – very different that B2C but very important

When we talk about CEM, we mostly give examples on B2C space.  But lately, there has been lot of interest on B2B segment and some CEM conferences have been held specifically focused on B2B CEM.


I have been struggling to understand B2B CEM space and recently got an opportunity to perform CEM maturity assessment for a converged operator in Europe, struggling with customer experience with their large customers, especially when they wanted to new converged offering to their customers, upgrading legacy solutions.  Here are my key takeaways from the the conference –


  1.  Business Continuity, Productivity and Security are top requirements in B2B CEM
  2. Understanding buyer personas – which people are involved in buying process, what are theirs goals and preferences, how end user is not involved in the buying process
  3. Most B2B customers want some SLAs for their CEM but are not willing to pay for it.  But they might consider paying for additional services such as Security, Analytics
  4. Persoalised service and channels of engagement are important to consider when designing B2B CEM

Orange Business Services shared their research with IPSOS on B2B CEM –

  • Business Continuity in mind
  • Ease of doing business – New Service Activation, Support, Self Care (Turk Telekom mentioned that it took 19 steps to change speed on a package!)
  • Value added services such as Analytics
  • Security of critical business resources and processes
  • Increasing Productivity of business

Vodafone raised issues of procurement for SME and large corporate customers.  Most interactions are with plan administrator and commercial with end users not getting represented properly.  The disconnect between admin and end user create problems when finally service is launch as end users are not aware of service catalogue, SLA levels and support agreements.  So understanding buyer personas and designing CEM fo them is pretty important.  A book Buyer Personas describes in details about buying process.

In terms of channels of engagement, large corporates have a dedicated account manager but he/she doesn’t have information on the customer experience or the SLA of the customer.  If you can’t measure it, you can’t manage it.  For SMEs, collaboration with local partners known to SMEs in a given area should be considered.  Local partners knows more about localisation of service.  Shop within a shop for SMEs might be considered as done by Proximus in the Netherlands.

Very interesting discussions on the SLAs – most customers won’t pay extra for SLAs as they have higher expectations from supplier.  In fact, a few customers mentioned that they would put CEM SLAs as a condition of contract.  So SLA offering and management for CEM is not longer a value added service….

For vendors supplying CEM, internal organisational changes are needed to better serve B2B customers.  TDC Denmark has developed industry specific teams to serve its B2B customers.  SoHo and SMEs are integrated into Proximus’s consumer business to better serve them.  Internal awareness of B2B CEM SLAS through Digital dashboard can be improved as tried by Turk Telekom.

In essence, B2B CEM is different than B2C CEM and operators have to make changes in their approach, organisation and channel engagements to better serve B2B customers.




How bad multi-channel experience ruins the brand?

All brands, in all verticals, are getting into multi-channel customer engagement due to customer’s multi-touch journeys across channels and not doing so will give competition advantage over you.  However, doing it wrong will cause more damage to you than not doing it at all!


My recent experience with American Express in India is a case to this point.  I have been Amex platinum customer for past 6 years and had some bad experiences with them – bill sent to wrong address, bill signed by security person not authorised to sign, food offers not sent on time and so on.  But they are on their way down in terms of customer experience and dealing with their customer complaints, without empowering employees to do anything about it.  This time, I called their contact center asking them about this year’s food offers.  First thing, I had to go through multiple security hoops despite validated on IVR.  Second, Amex told me they discontinued coupons to go green.  Though this is noble cause, not communicating to customers about this change of policy has done more harm to them.  Third, customer service asks me to go online again to search before I explicitly asked them to help me.


The website is so badly designed that it took me 5 clicks to see offers page.  Search function doesn’t work and typing “bangalore” didn’t result in any output.   Response to email complaint was done post 48 hours in which my name was spelled wrong.  So what does this tell you?  American express has not thought about proper multi-channel customer journey.  they haven’t designed online channel well and hence migrating customers to this channel for offers resulted in poor experience.  Since I went to online then to contact center and again contact center called to apologise, cost to serve went up, defeating the whole purpose of online.  Most important, I become their detractor now from promoter….that is bad given I spend at least $4000 a month on their card.  When I asked them to deliver a new card, they promised 2 days but card didn’t get delivered as their courier company couldn’t locate my address – this despite the fact that same courier company delivers my statements on time every month!


So how to fix this mess?  One, design customer journey and understand key moments of truth, across channels.  Process design alone is not enough as one can’t anticipate all permutations and combinations of customer demands.  So empowering front line employees is key to make decisions on the spot.  Third, clear, concise and timely communications with customers is critical.


I hope AMEX listens and changes!


Can a bad experience at moment of truth make you a detractor?

Recently on my trip to Bangkok, I had one of the worst experience in a 5-star boutique hotel.  I didn’t have 4 bottles of water I always ask, BBC channel was not working like last time, and I was made to wait at breakfast for 20 mins before I was even served a cup of tea!  In addition, AC stopped working and bathroom smelled bad.   It made me wonder whether I would go there again despite several goodies I received after I complained about it…


It made me think.  In my stay with hotels, what were the things for which my expectations were high and not met, and which are the things where my expectations were low and not met?  Also, is this repeat experience in near past or distant past?


I think when expectation are high, these factors are hygiene factors.  Good experience on hygiene factors is not going to make me wow and unlikely for me to tell 10 others.  These factors vary for different personas.  Certain factors are common for all personas – clean room, clean bathroom, working AC or heater, decent breakfast.  For business traveler and premium member like me, fast check in and check out and access to business center are hygiene factors.  Personal recognition ( recognizing by name as I am frequent visitor) and specific preferences in the room such as additional water and fruits are also hygiene factors for me.  Things such as complementary booking to a restaurant or a show, complimentary limo pick up and drop off are delight factors where my expectations is low.


Now if you don’t deliver on moments of truth for hygiene factors, customer will get annoyed.  But if he is associated with you for decent amount time and he/she likes your brand, he or she would give constructive feedback and expect some concrete actions from the brand to fix.  He or she would give brand one chance.  But if he or she experiences similar issues on these hygiene factors repetitively and in short duration of time span, memory hasn’t faded and negative impact has compounded now, causing him or her to become detractor.


So repetitive bad experience on hygiene factors over a short memory time frame is the worst and brands must avoid it.  But how to ensure this?  One can do journey design, identify moments of truth, create metrics to measure, define actions and processes and so on.  But we can’t anticipate every situation, every permutations and combinations.  So empowering front line employees to take actions on their own good judgement is key.  This judgement is guided and framed by company’s Customer Experience strategy and culture.


I plan to give my hotel one last chance….else I am gone forever.