I recently returned from a visit to Call Center World in Europe, one of the largest trade shows covering customer relationship management (CRM), which is transitioning to customer engagement management (CEM). Far from CRM/CEM being just a front end to enterprise content management (ECM) case management, it was immediately apparent that CEM and ECM are overlapping when it comes to the management of customer relationships and can learn from each other’s experience. But, today, they tend to talk in different languages and come at the problem from different directions.
In the call center and CRM world, customer interactions are evolving from predominantly voice driven inputs to a mix of inputs from multiple channels (including, email, SMS and social media). As companies seek to reduce costs, the frustrations over calling customer service is causing customers to use voice less in their communications and move to using a mix of channels to communicate. At the same time, outbound sales calls can be more effective when combined with other contact elements. This enables the calling company to better understand and target the customer through mining of social media and other databases while analyzing and countering objections–preferably while the call is progressing.
While trying to improve the customer call center experience, vendors are starting to mine new data in order to provide real-time understanding and potentially predictive understanding of the customer’s wants and needs. We are now seeing terms like "Big Data" and "Multi-Channel Communications" being actively discussed under the moniker of CEM. Products are being developed and expanded to understand and deal with this new media in real-time. Some time ago, some CRM and call center vendors started to leverage voice to text recognition to manage routing–known as interactive voice routing (IVR) with Nuance becoming the predominant technology supplier of the voice recognition.
But this only manages routing, so to gain a better picture of the customer and be able to serve him better, the CRM and call center vendors are incorporating and leveraging voice biometrics so that they verify the caller, pull up a profile and/or provide security for transactions, such as funds transfer instructions. They are starting to use voice analytics and even sentiment understanding to assess how excited, interested or annoyed a customer might be. They are using natural language processing and semantic understanding to access information on what the customer wants in customer service applications. They are using speech analytics to better understand the tone of the conversation.
These systems are not being used only from information delivered via traditional landline phone and the cell phone but also from emails, Twitter feeds, Facebook, SMS and other channels in addition to historical data. Curiously, for the most part, these vendors do not consider paper or fax, the business process or management of the communications for records, which potentially have litigation or compliance ramifications! They also do not consider using these technologies in face-to-face customer/business environments, such as bank branches, in hospitals or for insurance adjustment.
These CEM solutions often manage several thousand concurrent interactions with the organization’s customers in real time, looking up information and displaying guidance, text or routing information on agents’ screens. IVR drives dynamic workflow based on a customer’s requests. Biometrics validate a customer and allow for automatic historical and contextual document retrieval even before the customer starts to talk.
Concurrent with this, we have ECM systems and case management solutions developing completely separately, but which are faced with the same need to extract data from customer interactions in order to process a transaction often in a face-to-face environment–such as by a loan officer in a bank, by an insurance agent or an admissions person.
ECM was born of the need to manage, route and store documents and records in business-to-business communications. Workflow rules leverage understanding of the documents to help manage cases, such as new account opening, claims or patient encounter records. But these are all related to the consumer–someone the call center business is intimately familiar with. At the front end, capture technologies in this environment are moving from back office batch-based solutions to real time–recognition technologies have reduced the need to key data and started to automatically classify incoming documents from multiple channels–whether mailed in paper, fax or email.
Regulatory, compliance and legal needs, which evolved from the records management industry, are behind much of the need to classify and understand documents. But increasingly, the understanding is used for routing decisions and to drive business processes, as well as to help build understanding of trends within analytics and business intelligence. Data extraction from the semi- and unstructured documents that interface with the business process becomes critical, but usually, this is performed after the documents are received rather than when they are received or when in customer-facing environments.
The ECM industry has now started to look at emails and fax as incoming sources of documents, and now, the ECM industry is faced with managing social media and attachments to email, which may contain images or voice. Mobile phones and tablets are being used to send in photos of documents, SMS and voice annotations via multiple channels. Classification within document capture solutions is looking at the structure of documents, analyzing the text and starting to use natural language and semantic understanding to improve indexing, retention and routing decisions.
ECM capture recognition may be from voice, text or images from emails or other social media, but the subsequent processes, whether CRM related or document and records’ management related, need to be managed in real time and increasingly involve customer interactions. This is close to the world of CEM.
In this exploding world of Big Data, the companies that will win are those that can process information and react to their customers faster than their competitors. In this context, the CRM and call center people have an advantage in that they are used to working in a real-time environment, but they do not understand business processes and the software does not handle anything beyond managing customer interactions. They have built some workflow, but it does not have costing information. It is built around the need to route customer inquiries, not to process transactions. Most of their interactions are person to person–mainly consumer to business. But there are some “B to B” situations (as well as, “B to G” and ”G to B”).
In summary:
In the call center and CRM world, customer interactions are evolving from predominantly voice driven inputs to a mix of inputs from multiple channels (including, email, SMS and social media). As companies seek to reduce costs, the frustrations over calling customer service is causing customers to use voice less in their communications and move to using a mix of channels to communicate. At the same time, outbound sales calls can be more effective when combined with other contact elements. This enables the calling company to better understand and target the customer through mining of social media and other databases while analyzing and countering objections–preferably while the call is progressing.
While trying to improve the customer call center experience, vendors are starting to mine new data in order to provide real-time understanding and potentially predictive understanding of the customer’s wants and needs. We are now seeing terms like "Big Data" and "Multi-Channel Communications" being actively discussed under the moniker of CEM. Products are being developed and expanded to understand and deal with this new media in real-time. Some time ago, some CRM and call center vendors started to leverage voice to text recognition to manage routing–known as interactive voice routing (IVR) with Nuance becoming the predominant technology supplier of the voice recognition.
But this only manages routing, so to gain a better picture of the customer and be able to serve him better, the CRM and call center vendors are incorporating and leveraging voice biometrics so that they verify the caller, pull up a profile and/or provide security for transactions, such as funds transfer instructions. They are starting to use voice analytics and even sentiment understanding to assess how excited, interested or annoyed a customer might be. They are using natural language processing and semantic understanding to access information on what the customer wants in customer service applications. They are using speech analytics to better understand the tone of the conversation.
These systems are not being used only from information delivered via traditional landline phone and the cell phone but also from emails, Twitter feeds, Facebook, SMS and other channels in addition to historical data. Curiously, for the most part, these vendors do not consider paper or fax, the business process or management of the communications for records, which potentially have litigation or compliance ramifications! They also do not consider using these technologies in face-to-face customer/business environments, such as bank branches, in hospitals or for insurance adjustment.
These CEM solutions often manage several thousand concurrent interactions with the organization’s customers in real time, looking up information and displaying guidance, text or routing information on agents’ screens. IVR drives dynamic workflow based on a customer’s requests. Biometrics validate a customer and allow for automatic historical and contextual document retrieval even before the customer starts to talk.
"In this exploding world of Big Data, the companies that will win are those that can process information and react to their customers faster than their competitors."
Concurrent with this, we have ECM systems and case management solutions developing completely separately, but which are faced with the same need to extract data from customer interactions in order to process a transaction often in a face-to-face environment–such as by a loan officer in a bank, by an insurance agent or an admissions person.
ECM was born of the need to manage, route and store documents and records in business-to-business communications. Workflow rules leverage understanding of the documents to help manage cases, such as new account opening, claims or patient encounter records. But these are all related to the consumer–someone the call center business is intimately familiar with. At the front end, capture technologies in this environment are moving from back office batch-based solutions to real time–recognition technologies have reduced the need to key data and started to automatically classify incoming documents from multiple channels–whether mailed in paper, fax or email.
Regulatory, compliance and legal needs, which evolved from the records management industry, are behind much of the need to classify and understand documents. But increasingly, the understanding is used for routing decisions and to drive business processes, as well as to help build understanding of trends within analytics and business intelligence. Data extraction from the semi- and unstructured documents that interface with the business process becomes critical, but usually, this is performed after the documents are received rather than when they are received or when in customer-facing environments.
The ECM industry has now started to look at emails and fax as incoming sources of documents, and now, the ECM industry is faced with managing social media and attachments to email, which may contain images or voice. Mobile phones and tablets are being used to send in photos of documents, SMS and voice annotations via multiple channels. Classification within document capture solutions is looking at the structure of documents, analyzing the text and starting to use natural language and semantic understanding to improve indexing, retention and routing decisions.
ECM capture recognition may be from voice, text or images from emails or other social media, but the subsequent processes, whether CRM related or document and records’ management related, need to be managed in real time and increasingly involve customer interactions. This is close to the world of CEM.
In this exploding world of Big Data, the companies that will win are those that can process information and react to their customers faster than their competitors. In this context, the CRM and call center people have an advantage in that they are used to working in a real-time environment, but they do not understand business processes and the software does not handle anything beyond managing customer interactions. They have built some workflow, but it does not have costing information. It is built around the need to route customer inquiries, not to process transactions. Most of their interactions are person to person–mainly consumer to business. But there are some “B to B” situations (as well as, “B to G” and ”G to B”).
In summary:
- CEM is all about improving and reducing the cost of customer-to-business interactions
- CEM leverages voice recognition, sentiment analysis and speech analytics
- CEM is accessing and looking at social media
- CEM is integrating emails and chat into customer interactions
- CEM is a real-time system
- ECM is all about managing business transactions and compliance
- ECM leverages OCR, OMR and barcode recognition with semantic understanding
- ECM is accessing and looking at social media
- ECM is integrating email and fax into its workflow
- ECM understands compliance and records management needs
- ECM is a back-office system
As the world moves to real time and the need for real-time understanding of transactions increases, CEM needs to overlap with ECM capture.
This content originally appeared on Intelligent Understanding, the official blog of Harvey Spencer Associates. For more information, visit intelligentunderstanding.blogspot.com.
