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Optimising contact centre performance using behavioural economics
The document discusses the application of behavioral economics to optimize contact center performance, illustrating various successful case studies that demonstrate significant improvements in sales and customer behavior. It highlights techniques such as anchoring, the endowment effect, and the default effect, which have been used to influence customer decision-making positively. The research claims that implementing behaviorally informed strategies can lead to substantial increases in sales, customer engagement, and service efficiency.
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Optimising contact centre performance using behavioural economics
- 1. Optimising contact centre performanceusing behavioural economics “Oh, the Places We Will Go!” Conference 28 August 2017
- 2. WHO WE ARE: We'rea team of management consultants that specialise in human behaviour and thinking. We help businesses grow and become more profitable by effecting large-scale customer behaviour change using behavioural economics. OUR CLIENTS INCLUDE: 2
- 3. Table of Contents Introductionto behavioural economics Behavioural economics around the world Using behavioural to improve contact centre performance Our approach
- 4. Which table wouldyou prefer in your dining room? 4
- 5. In fact theyare identical - this is a visual illusion… 5
- 6. Behavioural economics, theconvergence of economics, psychology and sociology, studies human decision-making and takes seriously the fact that we often behave in consistent counter-intuitive, or irrational, ways 5 …decision-making has illusions too Would you rather take a certain $80… Or have a 85% chance of winning $100 and a 15% chance of getting nothing? Psychology of preferences
- 7. Heuristic example 1 7 Ratesof organ donation membership across a sample of European countries (Percentage of the population, 2008) 86% 100%100%100%100% 97% 100% 12% 17% 28% 4% Netherlands Belgium FranceAustriaGermanyDenmark United Kingdom Portugal SwedenPolandHungary Check the box alongside if you want to join the organ donation program Check the box alongside if you DO NOT want to join the organ donation program 1
- 8. 16% 0% 84% SCENARIO 2 Heuristic example2 8 68% 32% SCENARIO 1
- 9.
- 10. Some examples ofthese patterns include … Source: 1. Cognitive Bias Codex, 2016 10
- 11. Table of Contents Introductionto behavioural economics Behavioural economics around the world Using behavioural to improve contact centre performance Our approach
- 12. Organisations from aroundthe world have applied behavioural economics… 12 HSBC nudge app Lloyds Bank Money Manager JPMorgan Chase Financial Solutions Lab Barclays Bank Behavioural Finance Unit Discovery Health Vitality The Obama campaign The Behavioural Insights Team The Behavioural Economics Team #ogilvychange AIG Insurance Ipsos AIA Group
- 13. …and have achieveddemonstrable commercial success 13 The Behavioural Insights Team Lloyds Bank Money Manager AIG Insurance HSBC nudge app JPMorgan Chase Financial Solutions Lab Barclays Bank Behavioural Finance Unit The Obama campaign The Behavioural Economics Team #ogilvychange Ipsos AIA Group The Obama campaign Barclays Bank Behavioural Finance Unit • Addresses the behavioural nature of risk to achieve outcomes that are good for members, society, and insurers • Grows by 18% per year in new business Discovery Health Vitality
- 14. Table of Contents Introductionto behavioural economics Behavioural economics around the world Using behavioural to improve contact centre performance Our approach
- 15. CASE EXAMPLE 1: Increasedshort-term insurance sales by optimising the full leads process Proportion of leads that translated into a quote increased by 28%-points (Average transfer-to-quote ratio, 2015) 43,31% 53,92%41,97% 25%-3% 43.1% Overall increase in sales 25% 28% Endowment effect: “Some insurance companies overcharge by as much as 20%” Default effect: “Should we begin with your car, house or contents?” Anchoring: Agents pitch the premium at higher price by loading it at first Reciprocity: Allow one “discount” from the agent and one from the manager 31%16% 1,751,50 2,07 1,58 Average sales increased by 16%-points (Average sales per agent per day, 2015) 16% Historical (Six-month average) Pilot (One-month average) Historical (Six-month average) Pilot (One-month average) Lead warmers1 Sales agents2 TestControl TestControl TestControl TestControl 15
- 16. CASE EXAMPLE 2: Three-foldreturn on investment realised in two months Investment returns X X Total value of sales during pilot Expected value of sales without intervention Y 3.1Y 0,68X Multiple of actual sales from expected sales & ROI multiple The campaign had actual sales more than three times the value that was expected without intervention The client realised a 2.68 return on the investment of the project Project investment A behaviourally-informed script was introduced to an unscripted environment Agents were encouraged to drive conversations & aim for first-call resolution Focus on the structure of inbound calls optimised conversations Tools used for improved cross-sell ability in outbound calls Customer needs established created, analysed and satisfied Agent upskilling and supporting collateral was crucial for correct implementation of the script Examples of behaviourally- informed collateral 16
- 17. Applied behavioural techniquesto four key decision points throughout the transactional product/forex sales call CASE EXAMPLE 3: Improved the probability of a funded sale within retail bank’s contact centre Achieved a 45% increase in the likelihood of a funded sale with the new behaviourally-informed script The hook: “Are you happy with your current bank fees?” 1 Needs analysis: Understand upfront how the client would like to bank 2 Compliance: Distributed throughout script to limit cognitive strain 3 Product pitch: Value positioned in a way that resonated with clients 4 Test 5.2% 7.5% Control +44.2% Probability of success increased by 44.2% (% of conversations that resulted in a sale, 2014) 17
- 18. CASE EXAMPLE 4: Increasedsoftware sales in a highly competitive B2B telesales environment Four-step process aimed at improving software telesales performance in a B2B environment Sunk cost effect Default effect Negativity bias Analysed key insights from inbound and outbound calls Designed behavioural toolkit for inbound and outbound calls Interactive training aimed to embed key learnings One-on-one coaching with agents 1 2 3 4 R187 726 +29% Historical R241 273Pilot Performance increased by 30% (Three-month average) Average sales per agent increased by approximately 30% (Rand value of monthly sales per agent, 2014) (One-month average) 18 Selling multiple, complex software products Large and small ticket items Unscripted conversations
- 19. CASE EXAMPLE 5: Significantlyimproved conservation of retirement savings R297 805 R116 767 +155% 3M 0 2M 1M 7M 5M 6M 4M December January FebruaryNovember May The full roll-out of the new script resulted in a 155% increase in Rand amount conserved per day (Daily Rands conserved per agent, 2016) Performance during the pilot indicated that a 139% improvement in conserves in the long-term (Monthly Rands conserved per team, 2015) Control Treatment +139% Historical (Three-month average) New script (Two-month average) Behavioural toolbox Pilot results Roll-out results Expected result Actual result Positive framing Convert the call into a conversation about saving for a happy retirement, rather than being about a withdrawal 1 Anchoring Before telling the client the fund value, anchor the client on the savings value they should accumulate before retirement 2 …and others Herd effect, recency bias, hyperbolic discounting, etc. 3 19
- 20. CASE EXAMPLE 6: Increasein self-service channel usage at a large home entertainment provider • The Genesis team sought to change customer behaviour by encouraging customers to make use of self-service channels (such as the website, smartphone app) rather than the contact centre • Behavioural economics was used in scripting and process redesign to achieve a 146% increase in self-service usage Scripting Process redesign 1 2 Personalisation: “Customers like you are solving this query by…” Overall increase in self-service usage: 146% Assisted in breaking-down the learned behaviour of customers calling the contact centre in response to any issue Herd Effect: “Mr Smith, most of our customers are solving this query by…” 20 36% 32% 76% 90% Logins 146% Service queries Payment queries Transactions 100% Account queries Total queries 3
- 21. CASE EXAMPLE 7: Increasingsales by combining behavioural economics and big data 21 Process changes Increased campaign priority Four new lead-triggers were added to the three existing triggers, improving lead-quality for all agents Triggers were added to the dialler and made visible to all agents. This provided the agents with more context to the client and the conversation Total insurance sales per team (Monthly sales, 2016) 50 36 0 10 20 30 40 50 JuneMayAprilMarchFebJan ControlTest Pilot Historical underperformance of test team Pilot outperformance of test team Behavioural tools used in scripted conversations Difference in team sales performance per period (Monthly sales, 2016) 36 Control -50% Test 50 36 Control Test +39% Historical Pilot +89% Insights and actions Pilot results Avoid choice-overload by offering only the insurance product associated with the relevant trigger Herd effect: “We are able to find a lower premium for 60% of our clients” Anchoring: “We have two policies for you. The first costs R700 per month, the second is R200 per month” Process changes affected everyone 1 2 Exclusivity: “We are calling because you are an existing client”
- 22. Table of Contents Introductionto behavioural economics Behavioural economics around the world Using behavioural to improve contact centre performance Our approach
- 23. Our range ofservices is cumulative in a broader approach Rapid test Big bang 5-10 days 5-10 days 6-8 weeks 3-4 months 1-3 months 2-4 months 12+ months • Decision mapping • Behavioural research & insights • Behavioural analysis & segmentation Behavioural Analysis Behavioural- Change Design • Decision mapping • Behavioural research & insights • Behavioural analysis & segmentation • Nudge design • Loyalty & incentive design • Behavioural economics capability builds • Training in behavioural economics Capability Building Behavioural Prototyping • Nudge design • Loyalty & incentive design • Decision mapping • Behavioural research & insights • Behavioural analysis & segmentation • Field testing & piloting • Channel & campaign optimisation Timelines 23
- 24. Boitshepo Gaitate boitshepog@genesis-analytics.com +27(0)64 753 6538 For more information:
Editor's Notes
- #5 Alternative approach to visual illusion: When audience members are not measuring the tables on an A5 piece of paper
- #16 IWZ004: Sales Test & Learn Genesis Analytics was retained by a large insurance company to demonstrate how behavioural economics techniques can be used in their contact centre teams to increase the volume of new sales The volume of outbound sales is largely driven by two things: Lead warmer’s ability to transfer quotable leads Sales agent’s ability to convert a quote into a sale Lead warmer nudges: Endowment effect: “Some insurance companies overcharge clients by as much as 20%” Default effect: “Should we begin with your car, house or contents?” Herd effect: “We value all 17 million of our clients” This increased transfer-to-quote conversions of the test team relative to the control team by 28%-points Sales agent nudges: Anchoring: Pitch premium at higher price by loading it at first Reciprocity: Allow one “discount” from the agent and one from the manager Framing: “Will you be able to make a decision today?” Mirroring: Repeat customer’s words throughout call This increased average daily sales of the test team relative to the control team by 16%-points Overall, by optimising the full leads value-chain, we increased sales by 25% over the testing period
- #17 SPL004: Call centre scripting using the principles of behavioural economics Genesis Analytics was commissioned to apply behavioural economic to the unscripted environment in order to create a scripting and tools pack to assist agents to optimise their inbound and outbound calls The team’s objective was to increase outbound sales by developing and implementing an improved outbound call structure and script To achieve this, behavioural insights were used to design a customer centric call structure and script The agents were trained to focus on surfacing, solving for, and satisfying each client’s unique set of needs Total expected sales without the intervention: R237 418 Sales during pilot: R737 780 The pilot saw a 3.1 times actual sales value from what was expected (737780/237 418) Investment – R187 000, we added R500 362 more than they expected. This is a 2.68 return on investment within two months The agents within the telesales environment were unscripted, handle both inbound and outbound calls, sell both large and small ticket items and deal with multiple, complex products which require significant product knowledge. The Genesis Analytics team went through a multi-step process whereby they first listened to calls and engaged with the agent, quality control function and team management to better understand the nature of the environment and the calls. The next step was to formulate the tools to assist the agents by applying behavioural economic tenets and finally a process of training, agent coaching and change management was engaged in to ensure the learnings were ingrained with each of the agents. The team were also able to add value by providing advice in the following areas: team culture, team structure redesign, the on-boarding process and the incentive structure.
- #18 NED032: BE call centre - transactional product and forex sales In this project we worked with a retail bank’s contact centre sales team to increase the number of: Transactional product sales; and Forex sales. The outcome of statistical analysis suggests that the odds of a successful call increased by 45% using the new behaviorally informed script. This was achieved by applying behavioural economics to key decision points within the sales call. These key decision points included (not exhaustive): Hook: “Are you happy with the amount you are spending on bank fees?” (self-generation effect) Needs analysis: The questions centred on understanding how the client would like to bank Compliance: Compliance within a script is frequently burdensome. It was split throughout the script to make it less cumbersome. Product pitch: The value was positioned in a way that resonated with clients
- #19 SPL001: Behavioural economics call centre scripting The agents within the telesales channel of a large software company: Having unscripted conversations Handling both inbound and outbound calls Selling both large and small ticket items Dealing with multiple, complex products which require significant product knowledge The objective of the engagement was to increase sales figures by ensuring a greater number of quotes were converted into actual sales The following are some of the key behavioural economic tenets applied: Sunk cost effect: Increase cross-selling in the initial purchase Default effect: Increase the uptake of a service agreement and assist in closing a sale Negativity bias: Enhance customer satisfaction and loyalty Performance improved by almost 30% Relative to historical performance, the Rand value of sales increased by 29% over the one-month pilot period
- #20 OMG003 and OMG007 (Phase 1): Improving retentions in corporate exits When leaving their employer (resignation, retrenchment, etc.), corporate customers are given the option to either withdraw their retirement savings in cash or reinvest with Old Mutual Objective was to get corporate customers to reinvest (a greater portion) their retirement savings with Old Mutual A primary insight gained by the team was what we might call the “lottery effect”: Given the nature by which retirement deductions take place (before salary is paid each month), most customers are unaware of how much they have saved; The customers being called have just left their employer and are most likely in an uncertain space; When learning that they have this relatively large sum of money saved up, the customer feels like they have won the lottery, forgets the actual purpose of the savings fund (retirement) and starts mentally spending the money Working in the contact centre, the team focused on repositioning this conversation by: Reminding the customer that this money is intended for retirement; and Adjusting the customer’s perception of value Two primary nudges used: Positive framing: Convert the call into a conversation about saving for a happy retirement, rather than being about a withdrawal Anchoring: Before telling the client the fund value, anchor the client on the savings value they should accumulate before retirement Other nudges, including herd effect, recency bias and hyperbolic discounting were also used The new, behaviourally-informed script was first rolled-out in a pilot environment Pilot results indicated a 139% increase in Rand value conserved When rolled-out across the contact centre team, results showed a 155% increase in Rand value conserved per agent
- #21 MUL001a: Improving self service channel usage (and customer satisfaction) from within the call centre Voice over on project context: A large home entertainment provider had, over time, incrementally improved their call centre allowing them to achieve high customer satisfaction in this environment They quickly became victims of their own success, when, over time, this led to a large increase in call volumes and hence an increasing drag on the budget Voice over on nudges used: Primarily herd effect (social proof) Voice over on results: 146% increase in self-service usage