Why have a customer portal that is integrated to my CRM application??

As discussed in previous articles,

CRM is about acquiring and retaining customers, improving customer loyalty, gaining customer insight, and implementing customer-focused strategies. A true customer-centric enterprise helps your company drive new growth, maintain competitive agility, and attain operational excellence. “SAP

Before engaging with the customers, we should have some basic and general behaviours of our customers. I.e their age group, what generation category they fall into. Knowing some of this basic information like something along demographics….

  • How old are they?
  • What gender are they?
  • Where do they live?,

By understanding the demographics, the nature and buying behavior of the generation of buyers who will be our customers, the business will realize the increasing importance to use more technological savvy modes of marketing and communication.

The customers will be increasingly from the current Generation Y group. A brief explanation of the 3 major Generations will be discussed shortly.

born between 1946 – 1965 – The baby Boomers

born between 1966 – 1982 –  Generation X

born between 1983 – date – Generation Y

Baby Boom Generation is a term that portrays the people born during the middle part of the 20th century. The birth years of the Baby Boom Generation are the subject of controversy. Historically, everyone born during the post–World War II demographic boom in births was called part of the Baby Boom Generation.[1][2]

One of the features of Boomers is that they tend to think of themselves as a special generation, very different from those that had come before them. In fact, the Baby Boom Generation is often tagged “The Me Generation”. In the 1960s, as the relatively large numbers of young people became teenagers and young adults, they, and those around them, created a very specific rhetoric around their cohort, and the change they were bringing about.[5] This rhetoric had an important impact in the self perceptions of the boomers, as well as their tendency to define the world in terms of generations.

Generation X was coined by the Magnum photographer Robert Capa in the early 1950s. He would use it later as a title for a photo-essay about young men and women growing up immediately after the Second World War. The project first appeared in “Picture Post” (UK) and “Holiday” (USA) in 1953. Describing his intention, Capa said ‘We named this unknown generation, The Generation X, and even in our first enthusiasm we realised that we had something far bigger than our talents and pockets could cope with’.[7] Author John Ulrich explains that, “Since then, “Generation X” has always signified a group of young people, seemingly without identity, who face an uncertain, ill-defined (and perhaps hostile) future. Subsequent appearances of the term in the mid-1960s and mid-1970s narrowed the referent for “Generation X” from Capa’s global generation to specific sets of primarily white, male, working class British youth sub-cultures, from the spiffy mods and their rivals the rockers, to the more overtly negationist punk subculture.” [6]

The term was used in a 1964 study of British youth by Jane Deverson. Deverson was asked by Woman’s Own magazine to interview teenagers of the time. The study revealed a generation of teenagers who “sleep together before they are married, were not taught to believe in God as ‘much’, dislike the Queen, and don’t respect parents.” Because of these controversial findings, the piece was deemed unsuitable for the magazine. Deverson, in an attempt to save her research, worked with Hollywood correspondent Charles Hamblett to create a book about the study. Hamblett decided to name it Generation X.[8]

The term was popularized by Canadian author Douglas Coupland‘s 1991 novel, Generation X: Tales for an Accelerated Culture, concerning young adults during the late 1980s and their lifestyles. While Coupland’s book helped to popularize the phrase “Generation X,” in a 1989 magazine article[9] he erroneously attributed the term to English musician Billy Idol. In fact, Idol had been a member of the punk band Generation X from 1976–1981, which was named after Deverson and Hamblett’s 1965 sociology book—a copy of which was owned by Idol’s mother.[10]

In the U.S. Generation X was originally referred to as the “baby bust” generation because of the drop in the birth rate following the baby boom.[11]

Often defined as those born from 1982-2000, Generation Y’ers are growing up, and therefore becoming increasingly important in world affairs.

Gen Y is growing up. The oldest of the generation are now 26. They’re beginning to take to the workplace. As a result, a plethora of articles has turned up in business magazines worldwide, suggesting creative ways for employers to deal with this new, seemingly odd, generation. This article looks at who they are and why they matter.

This young generation is the first native online population. This alone has set the tone for how they act, react, and see the world. They are vastly different from their parent’s generation.

Ninety percent of Gen Y’ers in the US own a PC, while 82 percent own a mobile. And, perhaps not surprisingly, they spend more time online than they do watching TV.

Characteristics of Generation Y

They have grown up engaging with the Internet. This had led to their expectation of being able to obtain information at exceedingly rapid speeds.

Gen Y is also known for caring about the world and its problems, forming a large part of the worldwide Green movement.

Generation Y numbers is smaller than Generation X, or those born between 1961 to 1981. There are 78 million Gen Yers in the world. They make up about 25 percent of the US population. In some countries (ex. Iran), this percentage is much higher.

Understanding that our customers are more tech savvy, and internet depended, it is only logical to find ways and means to engage your customers through the internet, by implementing a customer portal that is integrated to your CRM application.

With a customer portal, your customers can get service on their own, 24 hours a day. They’ll get case updates and search the knowledge base, all without picking up the phone. Your customers and agents can even interact in ideas and answers communities. You’ll see loyalty go up while your service costs go down.

With a customer portal, your customers can log cases and get updates 24×7. All via an easy, user-friendly GUI and applications that can be run on mobile phones; all the methods which the current Generation is familiar and comfortable with.  The result: higher customer satisfaction at a lower cost.

Your business can grow by Connecting with Customers and Vendors through a Customer Portal.

A customer portal is a private, secure Website that enables businesses to share documents, calendars, and project information with customers. Commonly known as a customer extranet, a customer portal enhances customer relationships by providing complete 24×7 access to collaborative tools with just an Internet connection. It makes excellent business sense to use the customer portal as a means of getting and dissemination information to the customers, especially now that we have a better understanding of our customers.

Through a portal that is integrated to the CRM, a customer can raise tickets, view the solutions, check the products and services provided by the business, look up the FAQ to get their information, even chat online with the CSR. The customer can also update their personal information online, so its all done at their own pace and own time, you reduce the time and cost incurred to hiring people to telemarket and call customers, lets face many people, you and I included hate getting calls from telemarketers, this is a perfect solution for this.

This current generation of customers expect access to the most reliable, accurate, and up-to-date information. A customer portal provides a cost-effective solution without the anxieties and costs inherent with supporting complex virtual private networks (VPN). Provide each customer with access to an online portal to share important project documents, schedules, billing notices, and much more.

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Why Data mining in CRM?

“CRM is about acquiring and retaining customers, improving customer loyalty, gaining customer insight, and implementing customer-focused strategies. A true customer-centric enterprise helps your company drive new growth, maintain competitive agility, and attain operational excellence.” SAP

Customer Relationship Management (CRM) is a business philosophy involving identifying, understanding and better providing for your customers while building a relationship with each customer to improve customer satisfaction and maximise profits. It’s about understanding, anticipating and responding to customers’ needs.

To manage the relationship with the customer a business needs to collect the right information about its customers and organise that information for proper analysis and action. It needs to keep that information up-to-date, make it accessible to employees, and provide the know how for employees to convert that data into products better matched to customers’ needs.

The secret to an effective CRM package is not just in what data is collected but in the organising and interpretation of that data. Computers can’t, of course, transform the relationship you have with your customer. That does take a cross-department, top to bottom, corporate desire to build better relationships. But computers and a good computer based CRM solution, can increase sales by as much as 40-50% – as some studies have shown.

This is where Data Mining, Artificial Intelligence, and intelligent search applications come in. Wait, back up a minute, what are all these terms, you ask…

A good CRM application will provide the facility for the business to store and manage data they collect on their customers, and products. A better CRM will have the ability to group the data, convert them to information and display them in its search results whenever a user types in a word that may match the group of keywords associated to the question.

Okay, before we proceed, let’s get an understanding of what data mining is about…

Data mining, a branch of computer science[1] is the process of extracting patterns from large data sets by combining methods from statistics and artificial intelligence with database management. Data mining is seen as an increasingly important tool by modern business to transform data into business intelligence giving an informational advantage. It is currently used in a wide range of profiling practices, such as marketing, surveillance, fraud detection, and scientific discovery.

The related terms data dredging, data fishing and data snooping refer to the use of data mining techniques to sample portions of the larger population data set that are (or may be) too small for reliable statistical inferences to be made about the validity of any patterns discovered. These techniques can, however, be used in the creation of new hypotheses to test against the larger data populations.

Basically data can be collected, they would just be random numbers and words. Arranging this data into meaningful information was a tedious and arduous task for people compiling the data. The theoretical knowledge from the statisticians were converted into programming languages and data mining applications were developed in due course.

The manual extraction of patterns from data has occurred for centuries. Early methods of identifying patterns in data include Bayes’ theorem (1700s) and regression analysis (1800s). The proliferation, ubiquity and increasing power of computer technology has increased data collection, storage and manipulations. As data sets have grown in size and complexity, direct hands-on data analysis has increasingly been augmented with indirect, automatic data processing. This has been aided by other discoveries in computer science, such as neural networks, clustering, genetic algorithms (1950s), decision trees (1960s) and support vector machines (1980s). Data mining is the process of applying these methods to data with the intention of uncovering hidden patterns.[2] It has been used for many years by businesses, scientists and governments to sift through volumes of data such as airline passenger trip records, census data and supermarket scanner data to produce market research reports. (Note, however, that reporting is not always considered to be data mining.)

A primary reason for using data mining is to assist in the analysis of collections of observations of behaviour. Such data are vulnerable to co linearity because of unknown interrelations. An unavoidable fact of data mining is that the (sub-)set(s) of data being analysed may not be representative of the whole domain, and therefore may not contain examples of certain critical relationships and behaviours that exist across other parts of the domain. To address this sort of issue, the analysis may be augmented using experiment-based and other approaches, such as Choice Modelling for human-generated data. In these situations, inherent correlations can be either controlled for, or removed altogether, during the construction of the experimental design.

Data mining commonly involves four classes of tasks:[12]

  • Clustering – is the task of discovering groups and structures in the data that are in some way or another “similar”, without using known structures in the data.
  • Regression – Attempts to find a function which models the data with the least error.
  • Association rule learning – Searches for relationships between variables. For example a supermarket might gather data on customer purchasing habits. Using association rule learning, the supermarket can determine which products are frequently bought together and use this information for marketing purposes. This is sometimes referred to as market basket analysis.

With technology growing in leaps and bounds, Data mining has been considered to be added into customer relationship management applications. Rather than randomly contacting a prospect or customer through a call center or sending mail, a company can concentrate its efforts on prospects that are predicted to have a high likelihood of responding to an offer. More sophisticated methods may be used to optimise resources across campaigns so that one may predict which channel and which offer an individual is most likely to respond to — across all potential offers. Additionally, applications could be used to automate the mailing. Once the results from data mining (potential prospect/customer and channel/offer) are determined, this applications can be programmed either automatically to send an e-mail or regular mail or with the few steps a user has to click a button and mails to customers can be sent in bulk. Of course, the issues of bulk mail and spamming should be given due consideration here, it would be at the onus of the business to ensure their mass mailing is not construed as spam.

Finally, in cases where many people will take an action without an offer, uplift modeling can be used to determine which people will have the greatest increase in responding if given an offer. Data clustering can also be used to automatically discover the segments or groups within a customer data set.

Businesses employing data mining may see a return on investment, but also they recognise that the number of predictive models can quickly become very large. Rather than one model to predict how many customers will churn, a business could build a separate model for each region and customer type. Then instead of sending an offer to all people, who are likely to appear on the search, it may only want to send offers to customers. And finally, it may also want to determine which customers are going to be profitable over a window of time and only send the offers to those that are likely to be profitable. In order to maintain this quantity of models, they need to manage model versions and move to automated data mining.

An example of a CRM application would be in a car manufacturing business (assuming they sell directly to end users). If they maintained a database of which customers buy what type of product, and when, how often they make that purchase, what type of options they choose with their typical purchase, their colour preferences, whether the purchase needed financing etc., the manufacturer knows what marketing material to send out, what new products to promote to each customer, what preferences/options may swing the sale, whether a finance package should be included in the marketing material and when would be a good time to target each customer. They could use the information to build a relationship with the customer by reminding customers of service dates, product recalls, and maybe even to send the customer a birthday card.

A good place to start would be to make a list of your objectives and the benefits your organisation hopes to achieve. When looking at CRM solutions you want to check the features and functionality “out of the box”

– customisation is all very nice but it takes time and may not be as easy as you think

– supported platforms in terms of hardware, operating systems, databases, online activities and online ordering systems etc., (not just your back office systems but third-party software you use too)

– integration with those systems

– global perspective

– price – preferably a one-off purchase price with no annual licence fee.

Therefore, if you are looking to grow your business in leaps and bounds, and you know the way to it is to grow your customer base, to improve your relationship with your customer, to actually be able to get insights on your customer buying behavior and pattern, then you need a CRM application.

Not just any CRM application. A CRM application that can collect the right information about the customers and organise that information for proper analysis and action. An application that is able to keep information up-to-date, is accessible to employees, and the employees have the know how for  to convert that data into products to better matched the customers’ needs.

The secret to an effective CRM package is not just in what data is collected but in the organising and interpretation of that data. Computers can’t, of course, transform the relationship you have with your customer. That does take a cross-department, top to bottom, corporate desire to build better relationships. But computers and a good computer based CRM solution, can increase sales by as much as 40-50% – as some studies have shown.


^ Clifton, Christopher (2010). “Encyclopedia Britannica: Definition of Data Mining”. http://www.britannica.com/EBchecked/topic/1056150/data-mining. Retrieved 2010-12-9.

^ Kantardzic, Mehmed (2003). Data Mining: Concepts, Models, Methods, and Algorithms. John Wiley & Sons. ISBN 0471228524. OCLC 50055336.

^ Alex Guazzelli, Wen-Ching Lin, Tridivesh Jena. PMML in Action: Unleashing the Power of Open Standards for Data Mining and Predictive Analytics. CreateSpace, 2010

^ a b The Data Mining Group (DMG). The DMG is an independent, vendor led group which develops data mining standards, such as the Predictive Model Markup Language (PMML).

^ PMML Project Page

^ Alex Guazzelli, Michael Zeller, Wen-Ching Lin, Graham Williams. PMML: An Open Standard for Sharing Models. The R Journal, vol 1/1, May 2009.

^ Y. Peng, G. Kou, Y. Shi, Z. Chen (2008). “A Descriptive Framework for the Field of Data Mining and Knowledge Discovery”. International Journal of Information Technology and Decision Making, Volume 7, Issue 4 7: 639 – 682. doi:10.1142/S0219622008003204.

^ Proceedings, International Conferences on Knowledge Discovery and Data Mining, ACM, New York.

^ SIGKDD Explorations, ACM, New York.

^ International Conference on Data Mining: 5th (2009); 4th (2008); 3rd (2007); 2nd (2006); 1st (2005)

^ IEEE International Conference on Data Mining: ICDM09, Miami, FL; ICDM08, Pisa (Italy); ICDM07, Omaha, NE; ICDM06, Hong Kong; ICDM05, Houston, TX; ICDM04, Brighton (UK); ICDM03, Melbourne, FL; ICDM02, Maebashi City (Japan); ICDM01, San Jose, CA.

^ Fayyad, Usama; Gregory Piatetsky-Shapiro, and Padhraic Smyth (1996). “From Data Mining to Knowledge Discovery in Databases”. http://www.kdnuggets.com/gpspubs/aimag-kdd-overview-1996-Fayyad.pdf. Retrieved 2008-12-17.

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2011 Trend….Implementing, using a CRM application as a business strategy

CRM seeks to re-create the position where you know your customer and understand what makes them tick. It uses the recent developments in software that allow mapping of complex transactions and relationships to give a holistic picture of a customer and, in theory, gives the client the same level of service through a range of possible channels.

Magic Johnson sums it up, “With businesses, you go to the same places because you like the service, you like the people and they take care of you. They greet you with a smile. That’s how people want to be treated, with respect. That’s what I tell my employees.. Customer service is very important.”

Peter Drucker drives it home, “The single most important thing to remember about any enterprise is that there are no results inside its walls. The result of a business is a satisfied customer.”

So what must my CRM application have???

  • Sales force automation

Sales force automation (SFA) involves using software to streamline all phases of the sales process, minimizing the time that sales representatives need to spend on each phase. This allows sales representatives to pursue more clients in a shorter amount of time than would otherwise be possible. At the heart of SFA is a contact management system for tracking and recording every stage in the sales process for each prospective client, from initial contact to final disposition. Many SFA applications also include insights into opportunities, territories, sales forecasts and workflow automation, quote generation, and product knowledge.

  • Marketing

CRM systems for marketing help the enterprise identify and target potential clients and generate leads for the sales team. A key marketing capability is tracking and measuring multichannel campaigns, including email, search, social media, telephone and direct mail. Metrics monitored include clicks, responses, leads, deals, and revenue. This has been superseded by marketing automation and Prospect Relationship Management (PRM) solutions which track customer behaviour and nurture them from first contact to sale, often cutting out the active sales process altogether.

  • Customer service and support

Recognizing that service is an important factor in attracting and retaining customers, organizations are increasingly turning to technology to help them improve their clients’ experience while aiming to increase efficiency and minimize costs. Even so, a 2009 study revealed that only 39% of corporate executives believe their employees have the right tools and authority to solve client problems.

  • Analytics

Relevant analytics capabilities are often interwoven into applications for sales, marketing, and service. These features can be complemented and augmented with links to separate, purpose-built applications for analytics and business intelligence. Sales analytics let companies monitor and understand client actions and preferences, through sales forecasting and data quality.

Marketing applications generally come with predictive analytics to improve segmentation and targeting, and features for measuring the effectiveness of online, offline, and search marketing campaign. Web analytics have evolved significantly from their starting point of merely tracking mouse clicks on Web sites. By evaluating “buy signals,” marketers can see which prospects are most likely to transact and identify those who are bogged down in a sales process and need assistance. Marketing and finance personnel also use analytics to assess the value of multi-faceted programs as a whole.

These types of analytics are increasing in popularity as companies demand greater visibility into the performance of call centers and other service and support channels, in order to correct problems before they affect satisfaction levels. Support-focused applications typically include dashboards similar to those for sales, plus capabilities to measure and analyze response times, service quality, agent performance, and the frequency of various issues.

  • Integrated/Collaborative

Departments within enterprises — especially large enterprises — tend to function with little collaboration.  More recently, the development and adoption of these tools and services have fostered greater fluidity and cooperation among sales, service, and marketing. This finds expression in the concept of collaborative systems which uses technology to build bridges between departments. For example, feedback from a technical support center can enlighten marketers about specific services and product features clients are asking for. Reps, in their turn, want to be able to pursue these opportunities without the burden of re-entering records and contact data into a separate SFA system.

For  any type of business, basic client service can be accomplished by a contact manager system: an integrated solution that lets organizations and individuals efficiently track and record interactions, including emails, documents, jobs, faxes, scheduling, and more.

These tools usually focus on accounts rather than on individual contacts. They also generally include opportunity insight for tracking sales pipelines plus added functionality for marketing and service.

  • Social media

Social media sites like Twitter, LinkedIn and Facebook are amplifying the voice of people in the marketplace and are having profound and far-reaching effects on the ways in which people make purchases. Customers can now research companies online and then ask for recommendations through social media channels, making their buying decision without contacting the company.

People also use social media to share opinions and experiences on companies, products and services. As social media is not as widely moderated or censored as mainstream media, individuals can say anything they want about a company or brand, positive or negative.

Increasingly, companies are looking to gain access to these conversations and take part in the dialogue. More than a few systems are now integrating to social networking sites. Social media promoters cite a number of business advantages, such as using online communities as a source of high-quality leads and a vehicle for crowd sourcing solutions to client-support problems.

Companies can also leverage client stated habits and preferences to “hyper-target” their sales and marketing communications.

Having a CRM application with the above mentioned features will not be enough and give the business overnight customer satisfaction for all its customers.

The business from its top management, all departments, and the front end staff need to use the application, need to be trained to use the application to improve their ability to keep the customer happy.

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CRM…What is it???

CRM is customer relationship management. Let’s face it, our business income is from customers, the business is concerned in getting their customers to be repeat buyers, but there is increasing stiff competition with competitors who have higher marketing budgets. Customers’ … Continue reading

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