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Not all data is created equal

Using a unique combination of AI and human intelligence we find and prioritise the conversation that requires your attention and action. By prioritising data in real-time we help you to mitigate risk, improve retention & acquisition rates and deliver superior customer experience.

Our data structuring process

Jane Doe

Thanks so much @[InsurCo] for sending me a mail that says my financial advisor had died, only to find out she resigned, and you say he has passed away. She is very much alive and I spoke to her last week, I’m deciding now if I should or shouldn’t continue with my policy, thanks so much

10.15, 4 October 2019
Determine sentiment
What is the sentiment towards InsurCo?
Identify risk
In what ways, if any, does this represent a risk to InsurCo?
Accusations of unethical behaviour
Information disclosure
Pricing / fees disclosure
Protests / boycotts
Security and privacy concerns
Determine journey stage
What is the customer journey stage?
Not a customer
New customer
Current customer
Churning customer
Determine channels
What channels are being discussed?
Mobile app
Online banking
Call centre
Discover topics
Which topics are being discussed regarding InsurCo?
Staff or contractors
Operating hours
Turnaround time
Customer service
Product quality
Environmental impact
Safety and security
Insurance excess
Changing cover
Billing or payments
Upgrades or downgrades
Spam or unsolicited contact

Harness the power of AI and human intelligence

Artificial intelligence (AI) plays a critical role in processing data at scale but is still not adept at understanding the nuances of human conversation. To overcome these limitations, we combine AI and human intelligence. Algorithms are used for certain preprocessing tasks and our Crowd of human contributors filter noise for the conversation that’s high risk, high value, and urgent.

AI plus human intelligence

The DataEQ Crowd is a proprietary crowdsourcing platform comprising trained and vetted local language contributors from around the world. Contributors are remunerated for executing micro-jobs that include the verification and categorisation of social media posts and other short-form texts.

Key output - Net Sentiment Metric

Achieve an authentic voice of customer

Net sentiment as a key metric

Structuring your online conversation yields a robust customer satisfaction metric known as Net Sentiment. Net Sentiment is an aggregated and real-time metric that is a critical component in the quest for an authentic and complete voice-of-customer measurement framework. It is calculated by subtracting the total volume of negative sentiment from positive sentiment.

Leading customer-centric organisations are using Net Sentiment to benchmark against both competitors and past performance, and as an alternative to traditional lagging metrics like Net Promoter Score.

Key output - Prioritisation

Save time and money: prioritise high-value interactions

DataEQ applies four meta tags to our data: Risk, Purchase, Cancel and Service. These ensure that you prioritise the most valuable customer interactions. These tags save you time and money. They direct you to the conversation, from within all of the social media noise, that’s high risk or requires an urgent response.

Read the introduction

  • Risk - Mentions that pose an immediate risk or relate to a regulatory framework (eg. TCF)
  • Purchase - Mentions from a prospective customer who wants to purchase your product or service
  • Cancel - Mentions from a customer looking to cancel their service or not buy from you again
  • Service - Mentions from a customer that require service or describe their experience

Methodology – RPCS

Learn more about our how we find value
in unstructured conversation

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