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inQuba: The Science of Retaining Customers in Financial Services & Insurance [Aus Webinar]

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inQuba: The Science of Retaining Customers in Financial Services & Insurance [Aus Webinar]

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This is the slideware that was used during the live webinar hosted by inQuba, in Australia, on the 4th December 2018. Webinar recording available here: https://youtu.be/olZdhRM62mk

Imagine you could anticipate customer churn before it happened.
A recent report by Bain & Co. asserts that churn is the result of a series of poor experiences and misadventures over a period of time, not a single poor experience. Most customers are already primed to leave when an attractive competitive offer presents itself. Also, the only solution is to focus on the entire customer journey, not just the most recent episode. Today's businesses need to expose the real experiences of their customers, predict those at risk and intervene with next best actions to ensure the customer sticks around. Acquisition remains expensive, and the value still lies in existing relationships.

Customer Journey Management introduces break-through thinking and techniques for churn anticipation, predictive risk profiling and interventions that will have a business-altering impact on keeping and growing customers.

WEBINAR SPEAKERS
Margot Birbeck - Director, inQuba Australia
Trent Rossini - COO, inQuba

WHY YOU SHOULD LISTEN
Our industry-expert speakers addresses the following:
How do you discover and visualize the real customers' and agents' journeys as they navigate your products and channels?
How do you anticipate customer churn, in real time?
How do you intervene in order to mend and recreate customer experiences
How do you do all this at scale?

For further information, please visit us here: https://www.inquba.com/
Mail us here: info@inquba.com

CONNECT
Facebook: https://www.facebook.com/inQubaCX/
Twitter: https://twitter.com/inQubaCX
LinkedIn: https://www.linkedin.com/company/inquba/

This is the slideware that was used during the live webinar hosted by inQuba, in Australia, on the 4th December 2018. Webinar recording available here: https://youtu.be/olZdhRM62mk

Imagine you could anticipate customer churn before it happened.
A recent report by Bain & Co. asserts that churn is the result of a series of poor experiences and misadventures over a period of time, not a single poor experience. Most customers are already primed to leave when an attractive competitive offer presents itself. Also, the only solution is to focus on the entire customer journey, not just the most recent episode. Today's businesses need to expose the real experiences of their customers, predict those at risk and intervene with next best actions to ensure the customer sticks around. Acquisition remains expensive, and the value still lies in existing relationships.

Customer Journey Management introduces break-through thinking and techniques for churn anticipation, predictive risk profiling and interventions that will have a business-altering impact on keeping and growing customers.

WEBINAR SPEAKERS
Margot Birbeck - Director, inQuba Australia
Trent Rossini - COO, inQuba

WHY YOU SHOULD LISTEN
Our industry-expert speakers addresses the following:
How do you discover and visualize the real customers' and agents' journeys as they navigate your products and channels?
How do you anticipate customer churn, in real time?
How do you intervene in order to mend and recreate customer experiences
How do you do all this at scale?

For further information, please visit us here: https://www.inquba.com/
Mail us here: info@inquba.com

CONNECT
Facebook: https://www.facebook.com/inQubaCX/
Twitter: https://twitter.com/inQubaCX
LinkedIn: https://www.linkedin.com/company/inquba/

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inQuba: The Science of Retaining Customers in Financial Services & Insurance [Aus Webinar]

  1. 1. The Science of Retaining Customers in Financial Services & Insurance Customer Journey Management – the Next Evolution of CX
  2. 2. TRENT ROSSINI COO, inQuba trent@inquba.com MARGOT BIRBECK Director, inQuba Australia margot.birbeck@inquba.com Welcome to our Webinar! The Science of Retaining Customers in Financial Services & Insurance Customer Journey Management – the Next Evolution of CX
  3. 3. #JoinTheJourney @inQubaCX
  4. 4. Why is Customer Retention becoming more & more difficult?
  5. 5. Customers Are in Control Choice. Customers have options. In Australia there are more than 1,000 deposit products on offer, 4,000 different home loans, 200 business loan products& 157 credit cards (Canstar) Motivated. People are actively looking for better deals. 30% of new home loans are people changing their mortgage provider 3 million Australians switched banks in the past 3 years. https://www.ausbanking.org.au/media/media-releases/media-release-2017/3-million-people-make-the-switch Easy. The effort and cost to switch is low. New market entrants such as fintech start-ups and mobile brokering apps offer reduced rates.
  6. 6. How it was…
  7. 7. Customer Experience today: user-driven based upon customer needs
  8. 8. Customer Experience today: omni-channel, event & data-driven Web E-mail Chat Social Media Cell Branch Telephone
  9. 9. Digitization has changed everything!
  10. 10. Digitisation Example: Discovery Bank
  11. 11. What does this mean for Executives?
  12. 12. The Business Case for Retaining Customers 1 It costs five times as much to attract a new customer than to keep an existing one The probability of selling to an existing customer 60 to 70% The probability of selling to a new customer5 to 20% 2 3 4 5 Reference: ttps://www.getelastic.com/customer-acquisition-vs-retention-infographic 44% 18% Companies with a greater focus on Acquisition Companies with a greater focus on Retention
  13. 13. So how do we Retain Customers?
  14. 14. New Customer Renew Cancel Lodge Claim Submit Documents Receive Approval Receive Payment Update Policy Details DeclinedEnquiry Complain – Call Centre Complain – Social Media Update Issues Policy Administration Manage Customer Experiences Across the Entire Journey
  15. 15. Scientific Approach to Customer Retention Profile Customers • Create a single view of the customer (transactional & relationship) • Profile customers using all available data – interactions, attitudinal, segments & personas • Operational customer ‘at-risk’ scoring Analyse & Understand • Analyse data to understand the events, paths, profiles and behaviors that drive retention • What causes retention and what are the things they do before they stay or go? • Which customers to retain? Act, Respond, Engage & Improve • Prioritise at-risk triggers • Design and execute service interventions to neutralize risk events, i.e. Immediate response to customer issues • Continuously improve Predict, Automate & Orchestrate • Proactively predict churn and automate interventions • Use machine learning and AI to orchestrate customer retention
  16. 16. Poll
  17. 17. inQuba Worldwide
  18. 18. FINANCIAL SERVICES INSURANCE RETAIL TELECOMS & ICT HOSPITALITY & LIFESTYLE
  19. 19. inQuba Thought Leadership Report: Listed amongst 18 CFM vendors that support VoC programmes through a broad capability set “inQuba offers a customer journey modeler, a GUI-based journey data modeler that captures customer journey data for each client…” Report:
  20. 20. inQuba Leads Across VoC & Journey Analytics Gartner Market Guide for Voice-of-the- Customer Solutions November 2018
  21. 21. Journey Management Approach
  22. 22. In order to do Customer Journey Management, you will need only three data points on each journey step. Transaction name Time Person Journey Management Components
  23. 23. Journey Management Approach Time you are able to individually identify a customer journey path for Bob, John and Mark. = Goal = Goal = Goal With transaction name, person & time Bob John Mark Person 1 Person 2 Person 3 Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction
  24. 24. Journey Management Approach Time Individuals bring their own context, experiences, preferences, history and sentiment. Business requires a real-time single view of every customer and the tools to engage them contextually = Goal = Goal = Goal Customers are individuals Bob John Mark Person 1 Person 2 Person 3 Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction
  25. 25. Journey Management Benefit Steps towards a customer’s goal Visualization of a customer’s path Dead-ends; CJM shows you loops The power to nudge Contextual real-time engagements All customers and not a sampleCustomer Journey Management Bob John Mark Person 1 Person 2 Person 3 Time = Goal = Goal = GoalTransaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction Transaction
  26. 26. Scientific Approach to Customer Retention Profile Customers • Create a single view of the customer (transactional & relationship) • Profile customers using all available data – interactions, attitudinal, segments & personas • Operational customer ‘at-risk’ scoring Analyse & Understand • Analyse data to understand the events, paths, profiles and behaviors that drive retention • What causes retention and what are the things they do before they stay or go? • Which customers to retain? Act, Respond, Engage & Improve • Prioritise at-risk triggers • Design and execute service interventions to neutralize risk events, i.e. Immediate response to customer issues • Continuously improve Predict, Automate & Orchestrate • Proactively predict churn and automate interventions • Use machine learning and AI to orchestrate customer retention
  27. 27. Profile Customers Systems View
  28. 28. Journey Design & Planning CEM Model Anchoring CEM model Quality attributes linked to experience & measured through survey questions Text analytics queries linked to the experience to anchor themes
  29. 29. inQuba Text Analytics Real-time, integrated Text Analytics, anchored to the steps of the CEM Model Journey Design & Planning Text Analytics
  30. 30. Card application Journey Analytics Dear Charlotte We would really value your feedback on your recent quote experience. Kindly take a minute… TransAtlantic Ins. Today, 15:30 inQuba CX Very good! Charlotte Weaver Today, 17:40 Automation & Orchestration Feedback Orchestration
  31. 31. Transactions from External Systems Example: LOB or Workflow Records Quantitative Feedback Qualitative Feedback Very good! Charlotte Weaver Today, 17:40 Wow @TransAtlantic, I’m a little frustrated by the slow pace of this claim… @charlotte99 Today, 15:40 External Internal Expired Transactions (no further action) Elapsed Period Data Fusion External & Internal Data
  32. 32. Data Fusion Single View of Customer Events • Customer ID • Email • Mobile Transactions • Customer ID • Email • Mobile Social Media • Profile IDs Customer Attributes Quantitative Feedback Dialogue responses Cases Conversations Text Profiling Transactional Information
  33. 33. Data Fusion Single View of Customer Events • Customer ID • Email • Mobile Transactions • Customer ID • Email • Mobile Social Media • Profile IDs Contact matching allows for the numerous instances of the customer to be connected across transactions, creating an unbroken view of their journey
  34. 34. Scientific Approach to Customer Retention Profile Customers • Create a single view of the customer (transactional & relationship) • Profile customers using all available data – interactions, attitudinal, segments & personas • Operational customer ‘at-risk’ scoring Analyse & Understand • Analyse data to understand the events, paths, profiles and behaviors that drive retention • What causes retention and what are the things they do before they stay or go? • Which customers to retain? Act, Respond, Engage & Improve • Prioritise at-risk triggers • Design and execute service interventions to neutralize risk events, i.e. Immediate response to customer issues • Continuously improve Predict, Automate & Orchestrate • Proactively predict churn and automate interventions • Use machine learning and AI to orchestrate customer retention
  35. 35. inQuba Analytics Analytical and Operational reports Journey Design & Planning Rich Analytics Research Apply Delivery Activate
  36. 36. Charlotte Weaver: cweav@email.com Spotting at-risk customers Text Analytics & Single View Assignee: Martha Willems Note: Hi Martha, kindly contact… New Case: Contact Customer Today, 15:41 Hi Charlotte, we’d like to assist you with your renewal and have assigned Martha Willems to help you personally. Can we have her call you today? TransAtlantic Ins. Today, 15:30 Yes please! ;-) Charlotte Weaver Today, 15:40
  37. 37. MiWay retain over half of at- risk customers that are actively identified and engaged! Retention-related complaints have also halved. 57% retention of identified at-risk customers
  38. 38. Journey Testing Optimisation Real Segmentation Customer journey insights 75% Promoters SELECTED PATH > Application (agent) > Accept quote (agent) > Docs (branch) 15% Detractors not likely to buy 10% Have stalled and nothing has happened
  39. 39. Journey Testing Optimisation Target Audience Creation
  40. 40. Scientific Approach to Customer Retention Profile Customers • Create a single view of the customer (transactional & relationship) • Profile customers using all available data – interactions, attitudinal, segments & personas • Operational customer ‘at-risk’ scoring Analyse & Understand • Analyse data to understand the events, paths, profiles and behaviors that drive retention • What causes retention and what are the things they do before they stay or go? • Which customers to retain? Act, Respond, Engage & Improve • Prioritise at-risk triggers • Design and execute service interventions to neutralize risk events, i.e. Immediate response to customer issues • Continuously improve Predict, Automate & Orchestrate • Proactively predict churn and automate interventions • Use machine learning and AI to orchestrate customer retention
  41. 41. Card application Journey Analytics inQuba Case Management Hi Charlotte, we see that you may need some help with your application. Can we give call..? TransAtlantic Ins. Today, 15:30 Assignee: Martha Willems Note: Hi Martha, kindly contact… New Case: Contact Customer Today, 15:41 Card application Yes please! ;-) Charlotte Weaver Today, 15:40 Automation & Orchestration Service Orchestration
  42. 42. Card application Journey Analytics inQuba Social Media Hi Charlotte, thanks for bringing this to our attention. We’ll call.. @TransAtlantic Today, 15:41 Wow @TransAtlantic, I’m a little frustrated by the lack of communication from you.. @charlotte99 Today, 15:40 Automation & Orchestration Service Orchestration
  43. 43. Card application Journey Testing Optimisation, Automation & Orchestration Journey Analytics inQuba Single View Subject: Charlotte, got two minutes? Hi Charlotte, we’re thrilled that you’ve successfully activated. We’d love to get to know you. Please click here.. TransAtlantic Ins. Today, 15:30 Charlotte Weaver CWeaver@email.com
  44. 44. Card application Journey Analytics inQuba Engage Subject: Charlotte, got two minutes? Hi Charlotte, we’re thrilled that you’ve successfully activated. We’d love to get to know you. Please click.. TransAtlantic Ins. Today, 15:30 Automation & Orchestration Engagement Orchestration
  45. 45. Journey Testing Optimisation Nudging High Risk Customers
  46. 46. Automation & Orchestration Engagement Orchestration Subject: Charlotte, this is for you Hi Charlotte, we see that you’re planning an international trip soon! You may be interested in our travel insurance which is available to you with a 30% saving this week only. Please click here.. TransAtlantic Ins. Today, 15:30 Event triggers - Internal - External Journey rules - Customers that submitted an online application AND - Customers that have submitted a quote AND - Customers that have not submitted documents Single View rules - Existing customers - Customers that have submitted a positive comment about the brand Event triggers, Journey rules and Single View rules all operate in concert in order to ensure highly personalized and contextual real-time communications
  47. 47. Automation & Orchestration Engagement Orchestration
  48. 48. Servicing Journey Analytics Automation & Orchestration Incentive Orchestration Subject: Charlotte, need some coffee? Hi Charlotte, we want to apologise for the delay and give you a Starbucks voucher to help you through the day! Sound good?! ;-) Please click… TransAtlantic Today, 15:30
  49. 49. Scientific Approach to Customer Retention Profile Customers • Create a single view of the customer (transactional & relationship) • Profile customers using all available data – interactions, attitudinal, segments & personas • Operational customer ‘at-risk’ scoring Analyse & Understand • Analyse data to understand the events, paths, profiles and behaviors that drive retention • What causes retention and what are the things they do before they stay or go? • Which customers to retain? Act, Respond, Engage & Improve • Prioritise at-risk triggers • Design and execute service interventions to neutralize risk events, i.e. Immediate response to customer issues • Continuously improve Predict, Automate & Orchestrate • Proactively predict churn and automate interventions • Use machine learning and AI to orchestrate customer retention
  50. 50. Machine Learning Context Descriptive Analytics “What happened?” • Dashboards • Operational reports • Exceptions Predictive Analytics “What will happen?” • Statistical Libraries • R and Python Models • Reliant on model training • Sentiment Analysis • Absent of actions Prescriptive Analytics “This is what you need to do” Journey = Action
  51. 51. Collect and Organise Data Normalise the Data Feed data in the machine learning platform Model and Learn Use the insights to trigger actions (comms and discussions) Monitor Effectiveness Refine Continuum of Capabilities Machine Learning Approach
  52. 52. Application (web) Application (branch) Application (agent) Accept quote (agent) Accept quote (web) Documentation (branch) Documentation (email) Accept quote (agent) Customer Group 1 Customer Group 2 Customer Group 3 Machine Learning Optimisation O1 I1 I2 V1 I3 I5 O1 = Purchase I1 = Gender I2 = Interest Rate Rating I3 = Value perception I4 = Needs match I5 =NPS Segment Definition: • Journey = D,E,E,D • 18 to 32 years • Initial channel = online • Policy = $80 to $120 • Product = Motor / Home I4
  53. 53. Automation & Orchestration Machine Learning inQuba Platform Events Rules engine Machine learning Subject: Charlotte, got two minutes? Hi Charlotte, we’re thrilled that you’ve successfully activated. We’d love to get to know you. Please click.. TransAtlantic Ins. Today, 15:30 Hi Charlotte, we see that you may need some help with your application. Can we give call..? TransAtlantic Ins. Today, 15:30
  54. 54. Prescriptive Analytics Machine Learning Prescriptive Model Optimisation Specific Escalations Specific Action Reports Specific Action Reports Specific Action Reports Specific Escalations Specific Escalations
  55. 55. Imagine you had the capability, across millions of clients, to see who’s on & off their journeys, & who’s cheering for you. Wouldn’t that be a game changer? That’s why we’re here.
  56. 56. www.inQuba.com

Editor's Notes

  • Please join the conversation while we’re talking and we’ll try to address as many questions as possible – use the hashtag #Jointhejourney
    Also feel free to follow inQuba on Twitter or Facebook: @inQubaCX
  • Ask the question in the session…
    [Pause for dramatic effect. Perhaps take a sip of your coffee..]

  • HOW IT WAS
    Objective: to be able to describe the old way of doing business (with a bank, in the example)

    I have to admit, I was born before the change of the century
    I remember a time when we went down to the local bank
    At the local bank we would greet Emily who knew the family well
    If we deposited money, she would write out our bank balances in a little book and if we withdrew money, she would also write that up
    If my folks wanted a loan, they would arrange a meeting with the bank manager at the main branch at the shopping centre and go and explain to him how the loan would be paid off.
    Having a personal relationship with the bank manager way critical
    Apples and Blackberries were fruits
    Facebook was an identikit collection used by the police
    An app was used to get membership to a golf club
    Opening windows was a means to solve the problem of not having an air conditioner


  • CUSTOMER EXPERIENCES TODAY: COMPLEX PRODUCTS
    Objective: contrast the ‘how it was’ with the possible complexity of today’s customer journeys as they deal with institutions. Customers today need to navigate incredible product complexity. Not only that, they not have a multitude of channels… 
  • CUSTOMER EXPERIENCES TODAY: MULTI-CHANNEL SERVICING
    Objective: display how our channel options are more numerous, and we channel hop. More channels to navigate products which are more complex.
    Customer have a number of channel options available to them. And they channel hop. And they use more than one at a time. So, they’re having to navigate infinitely more complex products while interacting with business through more channels than ever before.
  • Ask the question in the session…
    [Pause for dramatic effect. Perhaps take a sip of your coffee..]

  • Here are some of the stats you know about retention and acquisition. Acquisition is expensive and unlikely.

    So this is why your business is throwing so much attention at RETENTION, right? Wrong. Here’s what’s really happening…
  • Ask the question in the session…
    [Pause for dramatic effect. Perhaps take a sip of your coffee..]

  • Insurance Journey
    Positive experiences
    - Loyalty profile increases
    Negative experiences
    Risk profile increases

    Customers have journeys that impact their Loyalty / Risk Profile
    Insight / Measure – overlay data, interaction, attitudinal, social
    Interventions Close the loop on negative experiences
    Advanced analysis – understand drivers
    Nudges
    Orchestration – AI & machine learning
  • Reason to Believe
    Examples of retention in FS
  • REASON TO BELIEVE

    We’re everywhere
  • And we’re awesome
  • Increasingly, Journey Analytics has been taking centre stage within CX. And inQuba has been enjoying recognition in the space.

    More detail:

    FORRESTER
    Within the “Voice Of The Customer Vendor Landscape, Sept 2017” report.
    Listed amongst 18 CFM vendors that support VoC programmes through a broad capability set, sharing space with Clarabridge, Confirmit, MaritzCX, Medallia, ResponseTek

    GARTNER
    Within the “Market Guide for Customer Journey Analytics, Aug 2017” report
    Quote “inQuba offers a customer journey modeler, a GUI-based journey data modeler that captures customer journey data for each client…”

    AND WE’VE DEPLOYED OUR SOLUTIONS AT A NUMBER OF CUSTOMERS TO ACHIEVE GREAT RESULTS…..>>>>

  • Increasingly, Journey Analytics has been taking centre stage within CX. And inQuba has been enjoying recognition in the space.

    More detail:

    FORRESTER
    Within the “Voice Of The Customer Vendor Landscape, Sept 2017” report.
    Listed amongst 18 CFM vendors that support VoC programmes through a broad capability set, sharing space with Clarabridge, Confirmit, MaritzCX, Medallia, ResponseTek

    GARTNER
    Within the “Market Guide for Customer Journey Analytics, Aug 2017” report
    Quote “inQuba offers a customer journey modeler, a GUI-based journey data modeler that captures customer journey data for each client…”

    AND WE’VE DEPLOYED OUR SOLUTIONS AT A NUMBER OF CUSTOMERS TO ACHIEVE GREAT RESULTS…..>>>>

  • JOURNEY MANAGEMENT APPROACH. In order to do Customer Journey Management, you will need only three data points on each journey step.
  • Directly from Desan’s launch deck
  • Directly from Desan’s launch deck
  • JOURNEY MANAGEMENT APPROACH
    Directly from Desan’s launch deck
  • Reason to Believe
    Examples of retention in FS
  • The conceptual journey map is configured within the platform. It represents experiences, sub-experiences and touchpoints. Quality attributes and text analytics queries are linked to the nodes in order to anchor feedback to the right parts of the customer journey.

  • INQUBA CX – we may want to reach out to a customer with a survey when they reach a particular point, like a successful activation. Reaching this point may trigger a survey, depending on the configured rules. And here are a few product shots… survey builder and analytics
  • Four data types, in two categories, represented as a data-driven, real customer journey.
    IMPORTANT: the expired transaction is a non-action where time has elapsed, and action is not required.

  • The single view of the customer is built up during the data fusion process, assigning event, transaction and social media information to individuals.
    LINKED CONTACTS displays the various instances of the customer as the customer is presented through the data.
  • Still within Single View, contact matching allows for the numerous instances of the customer to be connected across transactions, creating an unbroken view of their journey. An integration with a 3rd party service called Full Contact fuels intelligent matching and matching suggestions. This creates a seamless path between all the things that customers do.

  • Reason to Believe
    Examples of retention in FS
  • INQUBA ANALYTICS ensures that all feedback, captured against the model (as displayed on previous slide), is aggregated and presented to the various areas of the business, with drill down capabilities.
  • We’ve helped MiWay to actively identify at-risk clients, engage them and then retain over half of them.
    Retention-related complaints have also halved.
  • When we connect all the dots in the data we end up with visual customer paths that look like this. It’s easy to isolate drop offs and recursive loops, and customers not reaching their goals.
    NOTE: the virtual transactions which are also displayed on the customer journey, which could be lack of progressed after a specified elapsed time.

    CLICK. We have the ability to COMPARE here too.

    CLICK. Here are example insights which we can gather based upon the comparison which we have selected.
  • Target Audiences can be created for the path selections made. Rules can then be associated with these audiences in order to trigger communications, cases, and other actions (detailed in the next section). These rules can apply to the audiences in the present, or to contacts who satisfy the audience definitions in the future.
  • Reason to Believe
    Examples of retention in FS
  • INQUBA CASE MANAGEMENT – the message is turned into a case which is then assigned to someone in the business who needs to contact the customer and resolve the issue within an SLA. The business was alerted of the situation due to elapsed time. The result of this should be to nudge the customer onward towards her goal, correcting her path.
    Prod shots show Cases dashboard and analytics.
  • INQUBA SOCIAL MEDIA – here, the customer reaches a point and tweets the business in frustration. The mention is picked up by the social media listening solution in the platform where a group of people are monitoring online mentions.
    Prod shots show tweet stream and analytics
  • INQUBA SINGLE VIEW – … and by responding the platform learns more about the customer and this adds to the single view of the customer. This information is all accessible to the rules engine for further comms etc.
  • INQUBA ENGAGE – the customer reaches and point in the journey where they qualify for a campaign. The specific journey was included in the target audience rules. This qualification logic is informed by MACHINE LEARNING. The customer responds to the engagement…
    The prod shots show the graphical user interface and the analytics available.
  • Target Audiences can be created for the path selections made. Rules can then be associated with these audiences in order to trigger communications, cases, and other actions (detailed in the next section). These rules can apply to the audiences in the present, or to contacts who satisfy the audience definitions in the future.
  • Event triggers, Journey rules and Single View rules all operate in concert in order to ensure highly personalised and contextual real-time communications
  • Personalisation samples
  • The inQuba platform boasts an integration with the WiGroup service and network, allowing you to offer and ensure fulfilment of vouchers as behavioural incentives. A broad network of service providers is available through the network.
  • Reason to Believe
    Examples of retention in FS
  • Azure Machine Learning, working in parallel with events and the inQuba rules engine results in highly personalised, contextual, real-time engagements and actions
  • LOVE THE JOURNEY

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