Richard Snow's Analyst Perspectives

Attensity Uses Social Media Technology for Smarter Customer Engagement

Posted by Richard Snow on Apr 23, 2013 10:55:18 AM

When I last wrote about Attensity I classified it as a “pure play” text analytics vendor, but the latest release of its product has lead me to revise my opinion. Its product Respond uses natural language-based analysis to derive insights from any form of text-based data and among other results can produce analyses of customer sentiment, hot issues, trends and key metrics. The product supports what Attensity calls LARA – listen, analyze, relate, act – which is a form of closed-loop performance management. It begins by extracting data from multiple sources of text-based data, (listening), analyzing the content of the data (analyze), linking this data with other sources of customer data, and producing alerts, workflows and reports to encourage action to be taken based on the insights (act).

An increasingly common source of text-based data is social media. The latest announced version of the productAttensity Respond6, adds additional capabilities to support special media and takes the “act” step further. It has a full Twitter firehose, feeds from most of the other popular social media sites (including Facebook, Google+ and YouTube) and APIs that can extract text from email, surveys, social media forums and blogs. Respond6 then uses natural language analysis to add context to the content, such as determining which words relate to a company (for example, Orange Inc. as opposed to the fruit called orange), different versions of the same name (AA and American Airlines), occurrence of entities (product or company names, locations and times), events, issues (“This product doesn’t work,” “My call to the contact center was a waste of time”), sentiment (“I love this product”) and intentions (“I plan to cancel my contract”). Using this analysis, the product’s rules-based engine determines the appropriate action to be taken to respond to the interaction (such as call the customer back or alert a supervisor). Rules can be set up to match any situation and can trigger a variety of actions, including write to another system, search for information, send out a survey to gather more feedback or ask for support.

Respond6 also can route the record of the interaction, along with other information needed to execute the action, to the person or system responsible for taking the action; for example, it could pass a tweet, with the tweeter’s influence rating, to a social media team to respond, or create a ticket in a CRM system so that a customer service representative would be told to respond. This routing of interactions and actions takes Respond6 beyond “pure play” text analytics and puts it at the heart of what is now being called omni-customer experience management –the movement to provide consistent, personalized customer experiences across multiple channels.

Attensity has also made some technical improvements to the product.vr_db_top_five_customer_service_challenges The architecture now supports multitenancy and automatic load balancing, which are especially useful in handling very large volumes of tweets. Reporting has been enhanced to include more visualization options, trend analysis, emerging hot issues, and process and performance analysis.

My benchmark research into the unified agent desktop shows that companies face several challenges in making customer service meet customer expectations. The two most common are that communications channels are managed as silos and that customer-related activities (such as handling customer interactions) are not coordinated across lines of business. These two factors alone make it hard for companies to provide high-quality, consistent experiences across all touch points and all forms of interactions. Respond6 has tools to analyze text-based interactions more effectively and also to enable better responses to them, especially social ones. I recommend that companies evaluate how it can support their efforts to improve customer engagement and the customer experience.


Richard J. Snow

VP & Research Director

Topics: Social Media, Customer Analytics, Customer Experience, Social CRM, Speech Analytics, Voice of the Customer, Analytics, Business Analytics, Cloud Computing, Collaboration, Customer Service, Call Center, Contact Center, Contact Center Analytics, CRM, Customer Performance Management (CPM), Text Analytics

Richard Snow

Written by Richard Snow

Richard leads Ventana Research’s Customer and Contact Center Performance Management research practice, which is dedicated to helping organizations improve the efficiency and effectiveness of managing their customers, throughout their lifetime and across all touch points, including the contact center. He conducts research exploring the people, process, information and technology issues behind customer operations management, contact center management, and customer experience management. He also works with senior business operations and IT managers to ensure that companies get the best performance from today’s highly complex application products. Richard has worked in management and consulting leadership positions in the technology industry including with Price Waterhouse, Sema Group and Valors. In his work, he has been involved with all aspects of delivering highly complex IT solutions to a variety of clients in the telecommunications, financial services and public sectors. Richard has specialized in delivering customer care and billing solutions for telecommunications operators, and several multi-channel contact centers for organizations in both the public and private sectors.