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IBM: Enhanced 360 Degree View - Bloor White Paper

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Originally Published on Dec 11, 2014
The concept of a 360° view, especially of customers, although it potentially applies to other things too, has been around for a substantial period of time. The idea behind the 360° view of customers is that the more you know about your customers the easier it will be to meet their needs, both in terms of products and aftersales care, and to market additional goods and services to them in the most efficient fashion. Thus a 360° view helps both in terms of customer retention and acquisition, as well as up-sell and cross-sell.
The concept of a 360° view was developed when most organisations were limited to information stored within their relational database systems, perhaps augmented by clickstream data and by information available from third parties, such as SIC codes, or location-based data. Today, we live in a very different world where there are far more sources of data that can be used to inform the organisations about customers. For example, we have call logs and emails that provide details about our previous interactions with that customer. Moreover, customers avidly pursue the use of social media (LinkedIn, Twitter, Facebook, bulletin boards and so forth) and are keen to express their likes and dislikes, their preferences, and their prejudices in these formats. These new types of data, whether internal or external, offer the possibility of expanding the concept of what might be termed the traditional 360° view into an extended 360° view. This is sometimes referred to as 720° view but this is geometrically invalid as a concept so we will focus on the former terminology: the extended 360° view.
In this paper we will discuss why we believe that extending the traditional 360° view makes sense and we will give some uses that demonstrate why the extended 360° view represents an opportunity, both for those that have already implemented a 360° view and for those that have not. We will also discuss some of the technological implications of moving to, or implementing, an extended 360° view.

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IBM: Enhanced 360 Degree View - Bloor White Paper

  1. 1. IBM: enhanced 360° view A White Paper by Bloor Research Author : Philip Howard Publish date : September 2014 WhitePaper
  2. 2. IBM is in the vanguard for what it calls an enhanced 360° view and it is clearly well positioned to capitalise on the future growth of this market Philip Howard
  3. 3. 1 © 2014 Bloor ResearchA Bloor White Paper IBM: enhanced 360° view Prologue The original version of this paper was published under the title of “Extending a 360° view” as a generic discussion about the advantages of implementing such a system, along with an outline of the technical requirements for doing so. Bloor Research has been asked by IBM to produce this customised version of that paper, which briefly considers relevant IBM technologies and solutions in the context of the require- ments discussed. Other than this prologue, the section that is specific to IBM, and the conclusion, this paper is identical to the original. We have called this paper “IBM: enhanced 360° view” as this (enhanced) is the terminology used by IBM
  4. 4. 2© 2014 Bloor Research A Bloor White Paper IBM: enhanced 360° view Introduction The concept of a 360° view, especially of customers, although it potentially applies to other things too, has been around for a substantial period of time. The idea behind the 360° view of customers is that the more you know about your customers the easier it will be to meet their needs, both in terms of products and aftersales care, and to market additional goods and services to them in the most efficient fashion. Thus a 360° view helps both in terms of customer retention and acqui- sition, as well as up-sell and cross-sell. The concept of a 360° view was developed when most organisations were limited to infor- mation stored within their relational database systems, perhaps augmented by clickstream data and by information available from third parties, such as SIC codes, or location-based data. Today, we live in a very different world where there are far more sources of data that can be used to inform the organisations about customers. For example, we have call logs and emails that provide details about our previous interactions with that customer. Moreover, customers avidly pursue the use of social media (LinkedIn, Twitter, Facebook, bulletin boards and so forth) and are keen to express their likes and dislikes, their prefer- ences, and their prejudices in these formats. These new types of data, whether internal or external, offer the possibility of expanding the concept of what might be termed the tradi- tional 360° view into an extended 360° view. This is sometimes referred to as 720° view but this is geometrically invalid as a concept so we will focus on the former terminology: the extended 360° view. In this paper we will discuss why we believe that extending the traditional 360° view makes sense and we will give some uses that demon- strate why the extended 360° view repre- sents an opportunity, both for those that have already implemented a 360° view and for those that have not. We will also discuss some of the technological implications of moving to, or implementing, an extended 360° view.
  5. 5. 3 © 2014 Bloor ResearchA Bloor White Paper IBM: enhanced 360° view The argument for an extended 360° view There are two major generic use cases for an extended 360° view: one for marketing, and one for call centre and other operatives working at the point of service. In either case the traditional 360° view of the customer is useful but it is a blunt instrument. You can ensure that you have information that is as accurate as possible about your customers, and it can span different divisions within your organisation, so that the information you hold is holistic. However, that information is not detailed enough to give you a complete picture. In the case of marketing, you cannot accurately target individual customers. What typically happens in most organisations is that struc- tured customer data is analysed inside a data warehouse or data mart and, as a result of this analysis, customers are categorised as belonging to particular segments of the market according to their income, lifestyle, educa- tional background and so forth. Marketing efforts are then directed towards particular customer segments. Unfortunately, such segments are not small—in the sense that there may be many customers in any particular segment—which is why we describe this as a blunt instrument: it is not the fault of the 360° view, it is simply that internal resources such as customer relationship management (CRM) systems, even augmented with third party data, are insufficient to provide the detail to create micro-segments. The ability to use unstructured data, whether internally collected data from call records or external data such as social media changes all of this. Thanks to the additional information, not to mention opinions, which individuals make available about themselves through conversa- tions with your call centre or via social media, it is possible to get to a much more granular level of marketing. In some cases it will mean the possibility of 1-to-1 marketing but even where that is not the case then much smaller segments will be possible in many instances. As an aside we should say that Bloor Research is not, and does not claim to be, any sort of specialist in marketing per se; however, we do understand that 1-to-1 marketing can be described as the holy grail of marketing: that you know enough about a particular customer that you can tailor offers to him or her that are completely specific to that person. The extended 360° view is what makes this possible and enables marketing programs that improve customer retention, customer perception and up-sell and cross-sell effec- tiveness. It is also worth pointing out that you need both the information from traditional CRM systems and unstructured information from internal sources or social media to make this extended 360° view work. With the former alone you get broad brush segmentation that is not sufficiently tailored to individual require- ments, and in the latter case you get banner ads for flights to Barcelona for weeks after you already went there and came back! While information gathered in call centres may contribute to marketing efforts and organisa- tions may make use of the information for such things as next best offer, there is an important case to be made for an extended 360° view supporting contact centre operations directly. In particular, the emphasis in these environ- ments is on first-time call resolution (because it is more cost-effective for your organisation and also because it pleases the customer). Unfortunately, call centre operatives often do not have access to all the facts when they are engaging with customers. They are typically limited to the confines of the CRM and/or MDM system in place, and they do not have a complete and holistic view of the customer, which results in less than optimal response. An extended 360° view should provide all the relevant information about that customer that is known by the company.
  6. 6. 4© 2014 Bloor Research A Bloor White Paper IBM: enhanced 360° view Extended 360° view use cases The idea of an extended 360° view is relatively new, so there are not a great many companies with implementations in place. However, there are several (in telecommunications, financial services and consulting, for example) within organisations that run customer engagement centres. These have not typically added social media or other external data to their existing 360° view yet, but have augmented their data with internal data sources that are unstruc- tured. Aside from these, the following are vertical examples of an extended view; most, though not all, of which have expanded their view of customer data with external data. A banking example This bank was consistently losing customers to one of its rivals. Moreover, these losses had spiked upwards and losses had stayed high. What it eventually discovered was that its rival was monitoring tweets from the first bank’s customers and whenever it found a negative comment would reply to the tweeter offering a free trial (and easy account transfer) to the second bank, which was resulting in the first bank’s losses. This is good example of using social media in its own right: imagine doing the same thing to your competitors, or having them do it to you. In response, the first bank of course started to monitor its customers tweets for itself and, linking this information to its CRM system, was able a) to understand whether or not it wanted to retain this client (he or she might, after all, be unprofitable as a client) and then b) to determine what compensation or next best offer it might make to help to retain that client. While this use case reflects one particular bank’s experience we are aware of other banks, across multiple continents, which are adopting a similar approach. A loyalty card example This case refers to a hotel chain that has a loyalty card programme. It too monitors social media for comments that its members might make but, in particular, it looks for comments from members about staying in other hotels that belong to other companies. Where this is the case, and where this hotel chain has one of its own hotels in close proximity to the one its member stayed in, it will contact the member to say, “Did you know that we have a hotel just down the block from where you stayed?” and perhaps offer an incentive. A home improvement store example This company runs a chain of home improvement stores and it uses the extended 360° view not just with respect to customers but also with regard to employees. In the former case, it monitors tweets for comments that suggest that the tweeter might be inter- ested in home improvements (they mention it specifically, they have just moved house, and so on) and, when they get a positive result, they compare this with their master data management (MDM) system, where their 360° view of customers based on internal, struc- tured data is stored. If the tweeter is known to the company then it will fire off relevant marketing offers to that individual. A financial services example This company provides retirement savings plans and other financial products. To make its representatives more efficient and effective during conversations with clients, the organi- sation is consolidating information from dozens of internal sources—unstructured comments from other interactions as well as structured data—into a unified view of that customer account. The representatives can then focus on the conversations with their clients rather than searching for information while they speak.
  7. 7. 5 © 2014 Bloor ResearchA Bloor White Paper IBM: enhanced 360° view A preventative maintenance example An example here is a Telco that is using preventative maintenance as a way to enhance customer retention by minimising outages, dropped calls and the like, with a resulting reduction in customer complaints. We also want to make the point that the extended 360° view is not limited to customers (or employees) and that it is not just social media that can be used to provide relevant exten- sions. For example, imagine that you are a plant hire company and that you hire out large items of construction equipment for prolonged periods of time. Your customers will expect you to maintain those vehicles or equipment in good running order (much like users of mobile networks). However, maintenance is expensive. Historically, maintenance has been provided every so many months or every so many miles. It will be more efficient to use sensors on the relevant equipment to collect information that can be analysed for preven- tative maintenance purposes so that mainte- nance can be done at the optimal and most cost-effective time to ensure that service level agreements are met. Note that this maintenance scenario poten- tially extends into many other areas. For example, when is it appropriate to get your car serviced? Time- or mileage-based servicing is inefficient and we can expect motor manufac- turers (alongside garages) to start offering this as a service. The same would apply to air conditioning servicing or boiler servicing, or anything else of that type. Moreover, once we start to get into servicing of products owned by consumers then we potentially circle back to CRM systems, social media commentary and so on to make further offers: for example, perhaps you’d like your car waxed while it’s in for a service, or how about some alloy wheels? Extended 360° view use cases
  8. 8. 6© 2014 Bloor Research A Bloor White Paper IBM: enhanced 360° view Implementing an extended 360° view There are two aspects to this: implementing the base 360° view and implementing the extensions—adding data from non-traditional sources—to it. Many companies will already have done the former but some will not and we expect the concept of an extended 360° view to encourage new companies to adopt this approach. We will therefore summarise the requirements for the base capability, for the benefit of new adopters. Existing users can skip to the section “Extending the 360° view”. The base 360° view There are two fundamental requirements for a base 360° view: • Pullingalltheinformationaboutthecustomer, supplier, employee, product, service or whatever together. Usually, this will be in a single place (a master data management hub) but data can also be left in different locations provided that appropriate tooling is in place to ensure that the data in those different locations is synchronised and consistent. This second approach may be implemented by means of a master data management registry or by other means. • All the information needs to be consistent (the same in every location where that is appropriate) and reliable. As far as relia- bility is concerned this will require data quality processes supported, preferably, by a data governance initiative. An important consideration is that while you want data to be as accurate, complete, and up-to-date as possible, this does not mean 100% accuracy. In practice, at least as far as consumers are concerned, perfect accuracy is not possible (because people move house, change their phone number, get married and so forth). In practice, the accuracy required will depend on the type of data and the use case: marketing, for example, may have less stringent requirements than use cases involving preventative maintenance. Note that in the previous discussions we mentioned CRM systems on several occasions, especially because these tend to be widely used in marketing environments. However, it is important to appreciate that CRM systems are part of the MDM ecosystem: they take data directly from, or share data with, the MDM environment, whether hub-based or registry-based. Note further that a 360° view on its own does not help much. If the point about a 360° view is that it enables targeted marketing (or service provision) then you also need to be able to perform analytics against that customer data. This means you can segment customers into categories so that the most appropriate offers are made to the most relevant customers. Extending the 360° view Extending the 360° view is essentially about enriching that view, making it more granular so that you can gain marketing or other efficiencies. There are various different sources of information that you might use to do this. Arguably the most obvious is call centre records: details of what the customer said, notes made by call centre operatives, and so on. Emails will be another rich source of information in which customers will express their opinions. In addition there is social media, which we have already discussed in some depth, but you might also want to make use of clickstream data (how the customer acted when he was on your web site), or how a customer is using your services. In the case of the latter this will depend a lot on the type of services offered. For example, in Telco you would want to know how individuals use their smartphones, what apps they use, where they travel, what restaurants they frequent, which theatres they visit and so on. On the other hand, in the case of smart metering, you would want to know what patterns of consumption each user exhibits. The question becomes: how do you get this data and how do you integrate it with your existing 360° view? Internal data is not a problem as you already possess this infor- mation, though you will clearly need some way of parsing emails, documents, call centre notes and so forth to extract relevant infor- mation. However, external data may be more difficult to handle. Consider the restaurants where customers eat. This may or may not be directly relevant to you: you may be in the restaurant business but more likely you want to use this information to get a better handle on your customer. If he or she hardly ever eats at restaurants, that tells you something about that customer that distinguishes him or her from someone who eats regularly at Michelin starred destinations or from those that eat at McDonald’s. On its own this doesn’t tell you much, but put it together with theatre
  9. 9. 7 © 2014 Bloor ResearchA Bloor White Paper IBM: enhanced 360° view and cinema visits, holiday destinations, hotels stayed in, overseas vacations, business trips, tweets about favourite TV shows, and so on and you start to build up a picture of your customers. The first step, as mentioned in the home improvement example above, is that you need to identify the customers to which the data belongs. In other words you need matching processes (typically part of data quality solutions) that can associate the information you are collecting with particular customers. Secondly, you need to cleanse this data. There is no point in just dumping all of this infor- mation into your CRM or MDM environment— on its own it means nothing—it is when it is put together and analysed that you can start to get a better understanding of that customer. It is analytics here that is important in the same way that analytics is fundamental to lever- aging a base 360° view. In the case of internal data such as call centre information, this will require text analytics. However, both machine- generated and social media data often contain duplicated data (think re-tweets) that needs to be de-duplicated. Textual information will need to be parsed and transformed into a consistent format and, in some cases, additional data preparation will be required before the data can be analysed. As an example of this, consider that most statistical algorithms will not run against data with empty (null) fields. In other words, some significant data quality processing will need to be applied to the data before it can be analysed. In so far as this analysis is concerned you could put the data into a conventional data warehouse or data mart for analytic purposes, but much of the data we are discussing comes under the popular heading of “big data” (actually, Bloor Research prefers the term “any data”, both because that captures the varieties of data types that may be involved and also because any data doesn’t neces- sarily imply that there is a lot of it: which there may not be). We do not need to rehearse here the arguments for and against the use of non-relational platforms (most popularly Hadoop), but we can say that these represent a low cost way of storing this sort of data while providing a platform for its analysis. Fortu- nately, the same sort of analytic tools that are used for analysing and segmenting customer data (say) in relational environments are starting to become available to run against Hadoop also. We should also comment that in some circumstances interesting information about customers may be embedded in very large volumes of otherwise uninteresting data: in this case it may make sense to use a stream processing solution that can extract relevant nuggets of information without having to store a lot of extraneous and unwanted data. Ultimately, then, the information that is going to be used to augment your master data management system is going to be summary data that provides a detailed profile of your customers, but without the minutiae of every single thing that you know about them. Perhaps the simplest way of achieving this is by extending either the MDM or CRM record with a series of attributes (income, education, relevant habits [eating out, theatre going and so on], employment and so forth) against which a score is assigned. This can be updated as new information is received. Based on this information, marketing will be well placed to identify individuals who might be susceptible to up-sell, cross-sell and so forth, as well as those susceptible to churn. However, it is not only aggregated data that will be used. In a call centre, for example, you may want to search through relevant customer emails or service records during a call. In this case you will need an interface that allows you to combine conventional data from your MDM or CRM system with other information that may need to be searched, navigated, or queried (depending on the type of data) in real time. There is no point in extending your base view if you do not have the ability to see and interact with this extended information as and when you need it. In the case of search, pre-defined indexes will often be needed for performance reasons. Moreover, performance in call centres is important more generally: if the service operative is accessing multiple sources of data about a particular customer while he or she is on the line, then the perfor- mance requirements for accessing that infor- mation are stringent: callers will not hang on for more than a few seconds before starting to get aggravated. Implementing an extended 360° view
  10. 10. 8© 2014 Bloor Research A Bloor White Paper IBM: enhanced 360° view Conclusion The idea of an extended 360° view is a new one and derives from the fact that non-traditional forms of information can be used to extend what was previously thought of as the single view of the customer (or supplier, or employee) into something more complete. From the examples discussed in this paper there is clearly potential for getting a better under- standing of customers by using this approach, and we would certainly expect companies to get closer to (if not actually achieve) 1-to-1 marketing when adopting an extended 360° view than with previous approaches. So there are clear benefits to an extended 360° view. Base capabilities such as master data management will need to be in place and the information in these systems can then be enhanced with facilities for capturing, analysing or searching, and appending the data that will be used to augment these systems, along with a suitable visual interface that brings all of this information together. Fortunately, the tools and techniques for doing this will often be in place already though they may need to be extended to cope with unstruc- tured information of various types (from call centres, emails, social media and so forth), as well as machine generated and other forms of non-traditional data. As we have seen, there are already companies moving to adopt an extended 360° view. All the evidence suggests (and there have been lots of surveys around this subject) that companies thatusetechnology(suchasanalytics)tobetter understand their customers outperform their competitors. Early adopters of an extended 360° view will get competitive advantages over their rivals and this will force laggards to adopt a similar approach or lose business. As a result, we expect the extended 360° view to have a major impact on the market in the years ahead. Perhaps surprisingly for such a large organisation, IBM is leading this trend. We say surprisingly because innovation is more often associated with small companies than large ones. However, in this particular case, you need a broad software stack to cover all of the requirements of an extended 360° view, so perhaps it is not so surprising after all. In any case, IBM is in the vanguard for what it calls an enhanced 360° view and it is clearly well positioned to capitalise on the future growth of this market. Further Information Further information is available from http://www.BloorResearch.com/update/2232
  11. 11. Bloor Research overview Bloor Research is one of Europe’s leading IT research, analysis and consultancy organisa- tions, and in 2014 celebrates its 25th anniver- sary. We explain how to bring greater Agility to corporate IT systems through the effective governance, management and leverage of Information. We have built a reputation for ‘telling the right story’ with independent, intelligent, well-articulated communications content and publications on all aspects of the ICT industry. We believe the objective of telling the right story is to: • Describe the technology in context to its business value and the other systems and processes it interacts with. • Understand how new and innovative tech- nologies fit in with existing ICT investments. • Look at the whole market and explain all the solutions available and how they can be more effectively evaluated. • Filter ‘noise’ and make it easier to find the additional information or news that supports both investment and implementation. • Ensure all our content is available through the most appropriate channel. Founded in 1989, we have spent 25 years distributing research and analysis to IT user and vendor organisations throughout the world via online subscriptions, tailored research services, events and consultancy projects. We are committed to turning our knowledge into business value for you. About the author Philip Howard Research Director - Data Management Philip started in the computer industry way back in 1973 and has variously worked as a systems analyst, programmer and salesperson, as well as in marketing and product management, for a variety of companies including GEC Marconi, GPT, Philips Data Systems, Raytheon and NCR. After a quarter of a century of not being his own boss Philip set up his own company in 1992 and his first client was Bloor Research (then ­ButlerBloor), with Philip working for the company as an associate analyst. His relationship with Bloor Research has continued since that time and he is now Research Director focused on Data Management. Data management refers to the management, movement, governance and storage of data and involves diverse technologies that include (but are not limited to) databases and data warehousing, data integration (including ETL, data migration and data federation), data quality, master data management, metadata management and log and event manage- ment. Philip also tracks spreadsheet management and complex event processing. In addition to the numerous reports Philip has written on behalf of Bloor Research, Philip also contributes regularly to IT-Director.com and ­IT-Analysis.comandwaspreviouslyeditorofboth“Application­Development News” and “Operating System News” on behalf of Cambridge Market Intel- ligence (CMI). He has also contributed to various magazines and written a number of reports published by companies such as CMI and The Financial Times. Philip speaks regularly at conferences and other events throughout Europe and North America. Away from work, Philip’s primary leisure activities are canal boats, skiing, playing Bridge (at which he is a Life Master), dining out and walking Benji the dog.
  12. 12. Copyright & disclaimer This document is copyright © 2014 Bloor Research. No part of this publication may be reproduced by any method whatsoever without the prior consent of Bloor Research. Due to the nature of this material, numerous hardware and software products have been mentioned by name. In the majority, if not all, of the cases, these product names are claimed as trademarks by the compa- nies that manufacture the products. It is not Bloor Research’s intent to claim these names or trademarks as our own. Likewise, company logos, graphics or screen shots have been reproduced with the consent of the owner and are subject to that owner’s copyright. Whilst every care has been taken in the preparation of this document to ensure that the information is correct, the publishers cannot accept responsibility for any errors or omissions.
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