CRM 2009 Forecast - Part 1 -Sticking My Neck Out

Usually, from year to year, you’ll see forecasts from Gartner, Forrester, IDC, Aberdeen and the like for whatever area of technology interests you. You’ll also see economic forecasts about the coming bust, bear, boom, bull market and these incredible charts which prove that the human species is pretty much incalculable despite the consistent and pretty peaks and troughs of the provided long term cycles. Personally, I have a really complex formula when it comes to my forecast, refined over years of research, observation and algorithmic application. It goes something like eu + gw (l*bl)/i = fw, where eu = eye use; gw = guesswork; l=luck; bl=blind luck; i=intuition and fw = forecast wisdom. Meaning these, like most all forecasts (I hear analyst bellows even as I say what I’m about to), even if they include cool lookin’ statistics or other comforting numbers, are based pretty much on observation and lucky or not so lucky guesses and have as much chance of being wrong as being right. I’m actually amazed that year after year, people pay attention to what we pundit-types say. I’m not sure I would. But faith goes a long way with our species, doesn’t it?

CRM 2009 Forecast: How’d I Do in 2008? Gimme A High Four!

Usually, when I begin my forecast for the coming year, I like to look at how I did the previous year - which is usually disconcerting to say the least. So, in honor of my first non-intro post for this ZDNET blog, I’m going to be nakedly transparent and show you exactly how I did from last year - with some self-congratulation and some self-deprecation. Both richly deserved. Its late enough in the year that I don’t think anything earthshaking is going to occur in the last six weeks of this year, but then again that’s a forecast isn’t it? So maybe I’m right - or maybe not. Here’s the original blog post link for you but I’ll reproduce most of it here with my responses to my individual forecast items. The numbers in front were my attempt at probability of occurrence according to my gut, which after a period of non-exercise (you don’t want to know why that is) is larger than its been for awhile. You can read about my “methodology” on the original post.

A tailor-made approach to customer relations (FT.com)

A tailor-made approach to customer relations
By Andrea Ayers, president of customer management for Convergys Corporation

Published: November 4 2008 16:24 | Last updated: November 4 2008 16:24

Customer service isn’t working; newspapers are filled with horror stories of agents without the training or inclination to do more than read scripted responses, while a recent Ofcom survey found that almost half of broadband customers felt dissatisfied with the customer services provided by their internet service provider.

Message boards, news site comments, letters pages – all regularly feature rants and complaints about the state of customer service. Sixty per cent of respondents to a recent bank survey found that staff working from a script failed to answer their questions, while 55 per cent felt they didn’t listen. What makes this sort of story baffling is the simple fact that it is much more expensive for companies to acquire new customers than keep existing ones. What is going wrong?

The problems are numerous and well-catalogued. Answers learnt by rote/script, poor technology that handicaps de-motivated agents, high staff turnover; and that’s before one considers the issues surrounding outsourced or offshore call centres, including prejudiced customers and language barriers. In customer service, as long as the customers are asking for something that fits in with standard processes, they will get what they want. Should their request be at all different to the norm, the system starts to break down and a seemingly positive customer experience can unravel.

We believe organisations need to move away from servicing the customer, and into the mindset of having relationships with them.

But what’s the difference? On the face of it, the two approaches appear to only contrast semantically. Yet the thought process behind the titles is completely different. At the heart of relationship management is the idea of providing a personal experience for every customer. This means much more than a cheery greeting, a conversation about the weather, and addressing them by their first name. Relationships, whether personal or professional, are fluid and ever-changing.

When it comes to serving one’s customers, it means adapting to the customer’s needs, often proactively, rather than having the customer adapt to the system. A relationship management-oriented approach entails abandoning the one-size-fits all model and replacing it with a tailored experience, making every customer feel as if his or her issues are the number one priority for the company at that time.

A nice idea, some will say, a good theory, but how does one put it in to practice? Having the thinking in place, the mindset, is half the battle. The other half is about technology and people, and getting the best out of both.

On the technology front, analytics offer the most important insights. A customer’s billing history, recent calls, complaints, even their age and profession, provide organisations with the means to build a vivid picture of their individual needs. In many organisations, this information largely sits untapped, in separate siloes of information. This is a missed opportunity. The trends contained in these data could tell you where your next complaint will come from, who likes to be contacted in which manner (and when), and, crucially, who you could target with which products (and what the pitch should be). In short, intelligent use of customer analytics can make sure customers’ expectations are met or even exceeded – and add to the bottom line in the process.

The second part of the process, people, relates to the customer service staff, the agents at the coalface. There can be few other areas of business that can have such an impact on performance, loyalty, and revenue and yet be so widely characterised by poor training and high staff turnover. In order to engage with customers and facilitate relationship management, organisations need agents who are well-motivated. Giving them the right training and technology are clearly important, but those organisations that really win at customer service do so by encouraging the agents themselves not only to go beyond the script but also to provide feedback on how the system can be improved.

With the right technology and the correct training, agents will have more confidence in their work and be more inclined to move beyond the formulaic to provide a better experience for customers. Agents with little understanding of the systems they use will be unable to offer anything beyond a word-for-word script, which, as previously stated, can infuriate customers and create a poor yet hard-to-forget impression of their employer.

By combining technological and human resources, organisations can move beyond offering a by-the-numbers-customer service and move into a bespoke, positive relationship management experience. By doing so, they maximise the potential for securing both continued revenue from loyal, returning customers, and also additional income through targeted up-selling.

This is just the approach taken by a global financial services institution which we helped bring a relationship management approach to bear on its business. We found that the agent’s ability to empathise with the customer’s needs played a key role in customer loyalty, so we concentrated our efforts on this aspect. The company made a number changes to its technology, and the role of its customer service agents. It implemented analytics tools which enabled it to build real intelligence into its service processes.

Meanwhile, on a people level, it altered its agent training processes and set new best practice benchmarks. The result was an immediate improvement in customer satisfaction scores, with customers reporting low levels of satisfaction decreasing by a third, and almost 90 per cent of customers reporting the highest level of satisfaction. High customer satisfaction scores are now the norm for this company, and it continues to monitor the customer experience in order continually to improve and develop its relationship management.

A positive customer experience is the goal of any approach to managing customer relationships. By focusing on the longer-term relationship with the customer, rather than more short-term measures, companies will not just enjoy better retention and higher satisfaction, they will also see many of these interactions turn into profitable repeat business. In today’s tightened times, there is no more important objective than this.
Copyright The Financial Times Limited 2008

CRM = Human Capital Management

CRM = Human Capital Management
By Justin Smith, VP of R&D, AIM Technology Ltd

Published: November 7 2008 15:37 | Last updated: November 7 2008 15:37

Customer relationship management (CRM) is regarded as “understanding the customer”, but many organisations and technology developers approach it as a data-segmentation and profiling exercise. I contend that effective CRM must also involve adopting a 360-degree view of the performance of the staff who manage customer relationships.

Managing customers is only truly possible through managing customer-facing staff. It is simply not possible to achieve effective CRM by only looking at one side of a multi-faceted issue. Systems and solutions geared to analysing customer data are only analysing part of the picture.

Overlooking how the staff who deal with customers are performing is perhaps the biggest issue affecting customer satisfaction. If maximising revenue from customers is an organisation’s objective then a simultaneous objective needs to be the maximising of service delivery to customers.

Metrics looking at staff performance need to be in place to support CRM. However, the step organisations need to take before implementing metrics is to think strategically about their business and how its aims and objectives are communicated internally. This ensures that each layer of an organisation is aligned to the same objectives and can be measured accordingly by the layer above it.

Many organisations fall down by prioritising short-term sales-focused measures versus a longer term, strategic approach to CRM. Metrics are too often thought up in isolation. Each particular operation within an organisation needs to think about itself in the context of the overall framework. Another good pointer to the establishment of good metrics is to consider that a metric measures a process. Without relating a process to a metric, no improvement can be concretely affected, measured or reported.

Once an organisation has defined its aims it can define ways of measuring key performance indicators (KPIs) and who owns them, using the threefold approach of metrics-drivers-owners. The drivers are the influencing factors on a metric – for example, the behaviours they encourage. Over time, behaviour influences quality of service and, consequently, revenue performance.

In the contact centre environment, team supervisors are the owners of the KPIs and consequently play an important role in coaching and mentoring the agents who are on the front line of handling customer relationships.

Supervisors should spend time each day making sure they are coaching, mentoring and empowering their teams based on a scorecard to appraise and monitor performance in managing customer relationships. Similarly, the frequency and regularity of coaching sessions can be monitored. Ideally, teams should consist of between eight and 10 people, with a manageable portfolio of products and services.

When done correctly, coaching in handling customers should take place throughout the working day. This makes agents’ performance reviews an ongoing exercise rather than something dependent on the supervisor hastily gathering fistfuls of data once per month/quarter. Management information that supports the efficient running of an organisation needs to be at the fingertips of those who need it and who monitor the staff looking after customers.

Taking a higher level view of how customer relationships are managed gives a wide perspective on the factors influencing those relationships. In a contact centre, effective measuring is achieved through a balanced indicator that looks at more than call handling time or average revenue. If a call is handled quickly, but unhelpfully, then the relationship with the customer may be harmed and the time the agent has spent could be self-defeating and counter-productive.

Contact centre agents should not be measured just on cross-selling or up-selling; in fact measurement should not be confined to any one part of the customer relationship. It takes time to embed and drive the business through a well crafted framework of metrics. To this end, contact centre management should not just look at absolutes at any point in time, but also measure improvements in an agent’s customer service performance between when they joined and a given point, as it takes time to bed metrics in.

Using business process oriented applications (eg coaching, quality monitoring) to know how calls are being handled can be followed through into the effect on product and service delivery and how this affects customers. Managing contact centre agents by giving them personal performance information on a dashboard motivates them in managing customer relationships.

Every agent of a particular type can be assessed in the same way, enabling organisations to measure improvements in their staff’s customer handling techniques as well as the amount of products they are selling. This blends “softer” metrics into the mix. The results of having procedures to monitor patterns affecting customer relationships and buying trends can be seen in the bottom line.

Human capital management is at the core of analysing performance and trends in customer relationships. A scorecard approach gives an end-to-end perspective, deeper and more detailed than the sales figure oriented approach of most CRM. Technology plays a vital part in the continuous gathering and analysing of management information, but it is the context of effective coaching and monitoring that enables it to improve staff’s relationships with customers.


AIM Technology is a provider of analytical performance management software solutions for contact centres and service organisations.
Copyright The Financial Times Limited 2008

Customer management: it’s still about the data

Customer management: it’s still about the data
By Tony Fisher, president and chief executive of DataFlux

Published: November 6 2008 16:19 | Last updated: November 6 2008 16:19

Since the inception of the database, companies have been seeking to use collected intelligence to give them a greater insight into their customers. The results of this insight are stronger customer relationships and the ability to better meet their needs.

We can use the retail sector as an example. Based on loyalty scheme data, we might know a customer purchases beer and regularly shops at a time which suggests he works a 9-5 job. This intelligence is then used to tailor marketing campaigns to him, perhaps offering a discount on a certain beer brand or extending free delivery of the goods to his home. The intelligence gained from similar profiles held in the data warehouse are then used to feed broad-reaching marketing campaigns that encourage all customers in each segment to purchase beer and other products at the supermarket chain. This analytical practice has been operating successfully for a number of years and business intelligence products have been guiding these decisions.

Sitting alongside this analytical intelligence of the customer is the notion of consistent interaction. For this consistency, many organisations today have turned to large CRM systems which operate on the premise of organising a company’s operational data to supply customer facing staff with a complete view of the customer so a personal service can be delivered. This would, it is argued, provide the company with the ability to treat each customer as an individual.

By having a consolidated record of previous purchases, customer complaints and personal details, each and every customer-facing employee can be confident they are fully familiar with all the relevant details for each customer interaction. The employee could even predict what the customer might want in advance to avoid customer churn and dissatisfaction.

However, for these sophisticated tools to work properly there is one common element that absolutely must be robust – the underlying data. Without a level of certainty about the data going into these systems, the conclusions drawn from the basic geo-demographic information, such as names and addresses, to the more involved complex behavioral data produced by loyalty card schemes, are rendered unreliable. This in turn means that the overall investment in the systems and schemes cannot be fully realised.

The rule of thumb is that, like most other business assets, customer data depreciates and requires investment to see a return. The shelf-life of a customer database is approximately two years. This means that of 100,000 customer records contained within a database today, only 50,000 would be accurate enough to feed a CRM system for marketing purposes by 2010. Lifestyle changes, such as marriage, divorce, relocation and job termination, must be taken into account. If a customer has more than one entry in the CRM system or database, it can unknowingly lead to multiple interactions with the customer. The real world manifestation of the duplication problem can be seen when a call centre employee doesn’t have the golden customer record and insight they need to resolve a complaint or to cross-sell a new product line.

Similarly, companies often have multiple applications running in disparate silos. The sales system, finance system, CRM system and data warehouse might not be linked in a meaningful way and could each contain a record for “John Smith”. Only by merging this data together can a truly effective understanding of Mr Smith and his requirements be gained.

The most innovative data-oriented customer management companies often rely on customer data in order to remain efficient, drive sales and ensure compliance. These businesses are constantly investigating new approaches to stay ahead of their competitors. Master data management (MDM) – described by some as a “data utopia” – manages data at the master level by creating a single data repository and ensuring the quality of the data throughout an organisation. Using this master repository, it is then possible to “feed” other business systems in real time and overcome the battle against silos. The development of service-oriented architecture (SOA) as a discipline has made it possible to establish data governance business rules that can be re-used across multiple systems. These rules help assure high quality data is delivered to each system, regardless of where it is located.

However, like many other areas of technology, successful data management relies on more than just having the right vendor and a well-engineered IT system. Maintaining accurate and high quality data demands the involvement of the wider business and non-IT staff, along with a clear set of policies. Only by agreeing on an enterprisewide definition of what constitutes a customer record can a company determine what important data should be stored.

It is this data that will be used to build the intelligence which will enable the company to deliver exceptional service, which in turn fosters loyalty and increased competitive advantage. It’s also worth mentioning that the departments that usually best understand a customer’s needs, pains and demands are sales and marketing, not IT. As such, a collaboration of IT and business functions are required to deliver data that makes a difference.

Data management is a continuous process and requires constant attention. But it doesn’t have to happen overnight. Start today by building data quality rules and checks into the business processes. Then, as systems are merged together, establish a real-time data quality firewall that can validate data at the point of entry. This will ensure its value from the time of collection until its relevance ceases. At the end of the process, the customer data will be clean and useful, allowing meaningful interactions with each customer and satisfying both the IT and business sides of the organisation.
Copyright The Financial Times Limited 2008