Monday, June 13, 2016

If Computers Could Read Your Customer Survey Responses…

If computers could read your customer survey responses …

Written by: Peter Elliot


            Well, it all depends what you mean by ‘read’. Such a small word that implies so much based upon context. If you told me you read this article, it means you understood it. When a machine ‘reads’ a file, it typically means load and scan. When a machine ‘reads’ a survey response, it scans it, and applies predetermined algorithms to the words. It cannot possibly understand the meaning of the text; if it did, it truly would be artificially intelligent             

            A few years ago I led a project to analyse the written interactions between support agents and customers to gain insights into the reason for the call. We set out to analyse a corpus of text-based interactions between customers and service personnel, derive the topics and themes of the discussions, and use them to understand more about the company’s products and why customers need to call regarding their use. Thanks to a great team of analysts and data scientists, we built a prototype and celebrated a 70% success rate. While this may not seem worth celebrating, in the world of text analysis it’s quite good.

             The methodology is complex, but here are the basic steps. The text is cleaned by removing words (stop words) that have less meaning, such as pronouns. Similar words, such as plurals, are merged by stemming (shortening) them. What is left is a dictionary of meaningful words which can then be analysed. Clustering algorithms then scan for words that commonly occur together, and these clusters are surfaced to a SME (Subject Matter Expert) who answers the question ‘ if you see these words together in a piece of text what topic would you think is being discussed?’ Their answer becomes a document tag, and common tags can be counted, and graphically displayed. To test the validity of the output, a sample of the tagged documents are read by a person who compares the tag to the text, and notes whether the tag correctly describes the subject. This is how we assessed our 70% success rate.

            We humans automatically make assumptions when reading text, and one of them is context. We know up front, for instance, whether the conversation is about a disk storage unit or a fridge freezer. Our SME automatically assumes this knowledge when assigning a tag. Machines know nothing about context unless we provide that information.
While the SME is asked to provide the understanding, the machine can apply it methodically to large numbers of conversations very quickly. The next nut to crack is to get the machine, based on past experience, to learn to apply the SME understanding and create the tag. One way this can be done is to record word clusters and associated tags in a database, and use a search algorithm, however it’s important to search by context to get meaningful results. A start has been made by some MiT researchers who have assembled an open database of word associations and topics called ConceptNet that can be looked up by other applications such as Luminoso, which uses ConceptNet to infer topics and themes without the need for human intervention.

            Companies such as Clarabridge and Medallia combine many of these techniques to turn pages of text, such as TripAdvisor comments, into quantifiable terms. Social media tools such as Attensity use similar tools to trawl through tweets and facebook posts to provide insights into what customers are saying on social media. Their products can also determine the sentiment of the conversation by looking for key words and other words they occur with. Bill Inmon’s Forest Rim Technology Textual ETL product uses a relational database to align the results of context, ontology, taxonomy and text processing techniques in a form that can feed directly to a visualisation tool such as Tableau or Qlikview.

             If computers could read and understand text, and tell us what the text was about, then they would be as intelligent as we are. Furthermore Stephen Hawking wrote “Success in creating AI would be the biggest event in human history”. Reading and understanding text is an essentially human characteristic. But there are many applications where it would be very useful to read text at machine speeds and be advised about the topics within it, and a 70% or higher success rate still provides useful insights that would otherwise require lengthy, tedious and maybe error-prone reading and notation by individuals, where the rate of return for the investment probably would not be acceptable.           

             My particular pursuit of text-reading technology arose from a desire to understand customers, why they call, and whether they are satisfied with the products they have bought. Consider the possibilities as this technology is enhanced, and that 70% success rate improves. In the Contact Centre we could obtain real-time customer satisfaction scores as our agent’s conversations are turned into text via text-to-speech applications, and analysed to indicate today’s satisfaction ratings and hot topics. Product issues could be immediately picked up and acted upon before other customers fall into the trap. Text Analysis technology is still very young, and as it develops has huge potential for improving Customer Experience measurement and analysis.

Peter Elliot is an experienced and professional consultant. Peter and his peers at The Taylor Reach Group, assist companies and organizations to overcome business, strategic and operational challenges in their call, contact center and customer facing organizations

via The Taylor Reach Group Inc.

Using an Omni-Channel Strategy to Drive Customer Loyalty

How Leveraging an Omni-Channel Strategy Can Improve Your Customer Experience 

By: Colin Taylor

Recently, I was asked to give a presentation at the SCORE Conference in Boston on the importance and benefits of using an Omni-Channel strategy to drive customer loyalty. The event was a success and contained a lively discussion about how organizations can leverage an Omni-Channel, contact center design to drive customer loyalty, customer experience and customer centricity.

Omni-Channel can certainly be a game changer for contact centers. Using this approach, it can;

· Deliver consistent service regardless of channel of interaction,

· Support differentiated service for different customer segments and different customer journeys,

· Be a highly effective tool to support CX, customer centricity, customer satisfaction, retention and loyalty.

However according to research today, less than 1% of all organizations have deployed Omni-Channel.  A much more common approach is using Multi-Channel, which more than 40% of contact centers have deployed with 23% stating that they are executing well. Some confuse or combine Multi-Channel and Omni-Channel, so perhaps a look at their definitions would help.
I would define each as follows;

Multi-Channel is the use of multiple channels (calls, chat, email, web, etc.) to provide service to customers. In practice, these conversations occur in discrete channels. 

Omni-Channel employs all of these channels, but rather than separate and discrete communication channels, Omni-Channel provides seamless switching between channels with real-time awareness and knowledge of all the actions in any channel. Omni-Channel is significantly more complex than multi-channel.

This complexity is often born primarily out of the cost and resource requirements associated with integrating many disparate systems. 

But is the investment worth it?
To determine the return on this investment, let’s examine the enhanced capabilities that Omni-Channel can enable:


How can Omni-Channel support customer segmentation?

Companies segment their customer base to better understand these customers. The overall objective of customer segmentation is to analyze your customers, find niche opportunities, and create a sustainable competitive advantage. Segmentation allows organizations to increase profitability by better understanding customer needs and providing the solution then to meet those needs. Different treatments are required for each segment. We can segment our customers in many ways, based on lifetime value, RFM (recency, frequency and monetary value), class of customer, geography, line of business etc.

With Omni-Channel, we can recognize customers based on their segment across all channels:

On Voice Calls: 

  • Higher call/service level priority
  • Routed to higher skilled agent
  • Better FCR,
  • Higher CSAT/CX scores
  • More Empowerment


On Emails: 

  • Higher Priority
  • Human intervention versus AI/auto response
  • Contact-able agent signature versus generic
  • More Empowerment

On IVR: 

  • Ability to bypass or short-cut based on caller ID or customer number

On Chat: 

  • Higher service level priority
  • Lower chat to agent ratio (1:1)
  • Routed to higher skilled agent
  • Better FCR,
  • Higher CSAT/CX scores
  • More Empowerment

On Social: 

  • Auto escalation to contact center
  • Human response
  • Recognition

Journey Maps

How can Omni-Channel support your customer journey maps?

A Customer Journey Map (CJM) represents the customer experience from the perspective of the customer. Journey Maps need to be created for all channels of interaction. By understanding the journey of the customer when interacting with the brand, store or contact center, we believe we should be better able to deliver the desired customer experience. The logic here is sound, the challenge is with execution. There has been much coverage of the challenges and flaws in the CJM process as outlined below;

• 34% of companies indicating that they have undertaken CJM.
• Only 2% of companies that have reported success with CJM.
• 13% of customers who say CJM worked for them, while72% of customers who said CJM missed their needs.

The above research notwithstanding, CJM is a great process for better understanding the process, steps and journey that the customer must go through in receiving service from our organization. Failure to conceive, design and execute underlies much of the dissatisfaction cited above. To design and create an effective CJM process you need to keep the following considerations in mind;

1. The CJM must represent your Customer’s perspective. –Do you really know what this is?
2. Use research. -Conduct surveys, research and talk to Customer’s to confirm your understanding.
3. Represent Customer segments. –Different segments may have different experiences, you need to map each one.
4. Include the Customer’s Goal or Objective. –The Journey must end with the Customer getting what they want.
5. Include all touch-points and channels. –Customer’s expect consistency across the organization and channels.
6. Respect ‘Moments of Truth’ and the Emotions they invoke. –A bad interaction can taint an entire relationship. Identify the Moments of Truth and pay attention to the Emotions.
7. Check Alignment to your Brand Promise. –Customers are savvy, they are constantly checking us to see if we are ‘walking the talk’ and delivering the ‘promise’ that our advertising has made

“Is the service we are delivering an accurate reflection of the Brand Promises we have made?”

Omni-Channel provides CJM the ability to validate, confirm or inform:

  • The accuracy of the customer perspective and POV
  • The segmentation accuracy and effectiveness
  • Catalogue the ‘Moments of Truth’ across all journeys and segments
  • Impacts of ‘Moments of Truth’ by segment, transaction and channel

Customer Experience

How can Omni-Channel support your customer experience?

According to Gartner “by 2016, 89% of marketing leaders expect to compete mostly on the basis of customer experience” We all know that the experience the customer has when they interact with our company, our stores or our contact center, impacts their views, opinions and perceptions of the brand.

Customers judge their experiences on many different levels and across many touch-points. Their expectations don’t differentiate between a retail or a contact center interaction. They expect us to know them at all locations and across all channels. Omni-Channel can help us to do that.

The formal industry definition for customer experience is;
“How customers perceive their interactions with your company.”

CX (Customer Experience) includes all channels of communications and interactions, as illustrated on the Venn diagram:

Customer Centric Model

How can Omni-Channel support your customer centricity?

Customer centricity involves;

• Letting customers define the engagement.
• What channels they want to use.
• What control they can exert over their engagement.
• Engineer problems out as much as possible (proactive notifications/actions.)
• Ability to self-serve when desired.

In short, customer centricity requires that we recognizing a full 360 degree view of the customer. Being customer centric means you listen and respond to what they are saying and are consciously acknowledging their importance in your interactions and business decisions.

Omni-Channel supports customer centricity and ensures it is;
1. More consistent experiences and interactions
2. Superior understanding and appreciation of the customer POV and issues or concerns
3. More detailed and applicable notes in CRM informs better recognition and future actions

In a contact center environment, the moments of truth can an interaction, or can consist of multi- micro moments on any given customer contact interaction, as illustrated in the graphic below:

At Taylor Reach we have developed a contact center variation on this model. Each CX interaction can be viewed across three dimensions that have the greatest impact on the customers’ perceptions, opinions and experience:

  • Emotional connection. The ability of the agent to ‘connect’ with the customer
  • Rational connection. The ability of the agent to leverage training, knowledge and skills to resolve the inquiry
  • Customer effort. How easy was the process of reaching the agent.

We know intuitively that better service and better experiences improve customer relationships and research backs up our perceptions. Medallia Analysis found that organizations with the best customer experience realized a 140% increase in sales  when compared to those with the poorest customer experience scores.

The reasons for improving the customer experience can vary from organization to organization, but broadly they include: Improving Customer Retention, Improving Customer Satisfaction and Increasing Cross-Selling and Upselling.

Customer interactions account for more than half of all customer interactions in many industries, including retail and financial services. The decision of a customer to interact with the center is often based upon the perceived complexity of the task at hand. While many of us are comfortable interacting on-line to discover rates, prices or to understand the return policy, we are more likely to desire a live interaction if we perceive the issue or situation to be complex.

We can look at the Customer Experience across different levels. For example, in the graphic here we see the Customer Experience measured at the Brand level, the individual Customer Journey level and the Interaction level.

Increasingly organizations are beginning to measure the Customer Experience in their contact centers.  Research conducted by Genesys showed how companies are executing this strategy. When asked ‘What metric do you use to measure customer experience and loyalty’  the responses were:

  • Customer Satisfaction 51%
  • Net Promoter Score (NPS) 26%
  • Customer Effort Score (CES) 17%

By understanding the capabilities of Omni-channel and the ways that Omni-channel can support related corporate priorities and initiatives such as customer segmentation, customer journey maps, customer centricity and customer experience, you are now better equipped to help position your organization to identify and understand the benefits and returns that can be achieved from an investment in Omni-Channel.

. Omni-Channel strategies support your overall related corporate priorities such as customer segmentation, customer journey maps, customer centricity and most importantly, the customer experience. Going forward, ensuring all of these initiatives are connected are one of the most important considerations to make when looking at the current channels you are employing. Leveraging Omni-Channel is the best method for delivering on your brand promise and optimizing operational performance.

Should you have any questions comments related to this post, please contact Colin Taylor directly at, or call at The Taylor Reach Group Inc. 1 866 334 3730 ext. 102

via The Taylor Reach Group Inc.