Personalisation session - Henley Business School
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This document discusses personalization across multiple channels including digital, social media, email, mobile, and in-person. It covers segmentation of customers, rules for eligibility and offers, and creating personalized content journeys. Examples are given of how online retailers like Very, Wine.com, and Room & Board implement personalization using customer data. The document then provides a structured approach to personalization including determining goals, creating customer personas, mapping the customer journey, identifying catalysts and intents, developing customer solutions, and planning content and measuring performance.
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Personalisation session - Henley Business School
- 1. Aly Richards Personalisation Henley Business School Aly Richards
- 2. Aly Richards Channels 1 Digital & Non-Digital 2 Segmentation 3 Web-pages Social Email Mobile Face-to-face TV Outdoors Advertising - programmatic Mutli- channel Omni-channel Inbound Outbound Above the line Below the line Personalisation - Three Questions Raw data Segment insights Demographics Needs based Personalisation on segments? Or at Segment level?
- 3. Aly Richards What do you mean by Personalisation?
- 4. Aly Richards Content 1 Offers 2 Actions 3 Propositions Variations & Configurations Bundles Rules – eligibility Predictions Personal content journeys “Dear Fred” Interests Needs Catalysts Engagement Above the line and below the line Personalisation - Three Areas Predictions Risk Retention Service Matrixed predictions Experiences
- 5. Aly Richards On-line Retail Examples
- 6. Aly Richards Very Very’s website has the built-in capability to deliver a staggering 1.2million different landing pages according to who’s looking. In this sense, it’s less of a website and more of a tailored online shopping experience; one that recognizes the differences between individual customers and visually reflects their personal preferences.
- 7. Aly Richards Wine.com Using feedback data to gain a deeper understanding of its customers and improve the relevance of its responses, this online wine retailer gets granular with meta tags that trigger inspiring suggestions for shoppers at its online store. Instead of an over-reliance on widely searched words such as red, white, and rosé, in an effort to further refine the relationship it has with its customers, wine.com has added more delicate references: smoky, flinty, crisp, sharp, bold, dry are just some of the descriptive words that spring to mind. In doing this, the brand has managed to differentiate itself significantly from other companies in the sector. By building a list of descriptive words and integrating them with its system, ready to tag browsers and buyers who pick them, wine.com puts itself in an ever-strengthening position to drive more and more meaningful future recommendations. At the same time, it has added an element of pleasant surprise for customers unknowingly in need of an online concierge.
- 8. Aly Richards Room & Board By combining siloed information from the online and offline parts of its business, then running the amalgamated data through a new system, the furniture retail company made some surprising discoveries about its customers. One was that many were disappointed that their own rooms never looked as complete as those on Room & Board’s website and in its physical store displays. With the help of the system’s intelligent learning algorithms, the company responded with a strategy that ensures customers receive regular ‘room completion’ recommendations. Following the purchase of a sofa, for example, customers next receive automated, tailored and targeted emails suggesting other items...a specific lamp to match that sofa, a suitable rug, cabinets, wall hangings...all within two months, to help the customer complete their vision. The interesting part is that those added ‘sales’ are more a by-product of better service provision, not a brazen drive to simply sell more. The company’s new approach worked. In the first three months of implementing the new customer- centric strategy, Room & Board had boosted the average value of its orders by 16 percent, and its ROI by almost 3000 percent!
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- 10. Aly Richards “But that is still a minefield to work out what personalisation I should do!”
- 11. Aly Richards Structured to approach personalisation…
- 12. Aly Richards What & Why?
- 13. Aly Richards Determine Goals Business commercial goals – E.g. Increase product penetration rate in segment X. – Increase sales of product Y. – Determine business issues or challenges that can be addressed with personalisation. (Such as product penetration, engagement or retention/relationship.) – Brand or Line of Business specific Business case – Opportunity upside – Costs of implementation – Restrictions and challenges
- 15. Aly Richards Personas (Build on segments) CATALYST 1 CATALYST 2 CATALYST 3 CATALYST 4 CATALYST 5 CATALYST 6 P O M PERSONAS Common ground Cause to engage Intent INTENT 1 INTENT 2 INTENT 3 INTENT 4 Commercial goal CUSTOMER ENGAGEMENT T H R E S H O L D Mindset change
- 16. Aly Richards Customer Intimacy Who is your ideal customer? What problem do you solve for them? What ambition/dream/goal do you help them realise? Why will they start a journey to select you? – What is their catalyst?
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- 18. Aly Richards Natural History Museum – Personas Examples
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- 23. Aly Richards Exercise 1 - Persona Template Pain & Frustrations Interests & Catalysts Fears & Implications Intent – Goals & Aspirations Leads to..
- 24. Aly Richards Catalysts Every journey has to start somewhere and we call these starting points the catalysts. The number of catalysts and the number of buying intents determines the actual variety of buying journeys your customers could be on. To build your list, think about your persona and then complete this sentence – “I need to….” Try and think of as many different reasons they would start a journey. You are not going to use all of these, they will be prioritised, but it will help you in writing different and new content.
- 25. Aly Richards Buying Intent By creating content based around your audience's buying intent you can ensure that you are supporting and discovering the actual reasons your customers buy your products or services. The second part of the sentence is - “in order to….”
- 26. Aly Richards Examples for Bananas – A musical Instrument Store
- 27. Aly Richards Customer Solutions Change the context of the offer – From functional context - shaving razor – closer, smoother – To application context – personal care - faster, healthier. – To enablement context – appearance – confident, professional Benefits not features Perceived value then price Offer sequence – Hook – Freemium – Core Proposition/Product – Premium Product
- 28. Aly Richards Exercise 2 - Customer Solution Template Persona Product – What it is Why this Persona uses it/buys it What it enables them to achieve (Intent) Catalyst Joe Bloggs Razor Personal Care Professional Appearance Job interview
- 29. Aly Richards How do I know if I have the right needs/catalysts? TEST WITH CONTENT –What do your customers engage with the most?
- 31. Aly Richards Customer Journey/Engagement Maps Act1: OrdinaryWorld Act1: CalltoAction Act1: Fear,Uncertainty& Doubt Act1: Proof Act1: Threshold Act2: Consider Act2: Compare Act2: Buy Act3: Receive Act3: Experience Act3: Acknowledge Act3: Advocate Call to Action Resistance ProofOrdinary World Threshold Consider Compare Buy Experience Acknowledge Advocate Marketing CustomerSales Receive
- 32. Aly Richards Personalisation & Journeys What personalisation's will help us to achieve the goal? Storyboard the journey with the personalisation in place – What does it look/feel like for the customer? – What does it look/feel like for the agent? What difference does this make? – Workshop with agent group to discover challenges or opportunities.Act1: OrdinaryWorld Act1: CalltoAction Act1: Fear,Uncertainty&Doubt Act1: Proof Act1: Threshold Act2: Consider Act2: Compare Act2: Buy Act3: Receive Act3: Experience Act3: Acknowledge Act3: Advocate Call to Action Resistance ProofOrdinary World Threshold Consider Compare Buy Experience Acknowledge Advocate Marketing CustomerEngage Receive
- 33. Aly Richards Time Ordinary World: Engagement & Exit Engage: Enter & Engagement Engage: Engagement Marketing CustomerSales Content brief for each piece of content created Customer content journey mapped Which feeds the creation of content to move your customer on their journey Storyboards
- 34. Aly Richards Exercise 3 - Taking your audience on a journey Ordinary world Engagement F, U, D Proof Threshold ACT1 Consider Compare Buy ACT2 Receive Experience Acknowledge Advocate ACT3 Deal with cynicism and resistance to change Core content they need to consider What should be done – the detail CREATE ADVOCACY MAKE THEM BUY ENGAGE YOUR AUDIENCE Hook your audience in Call them to adventure – “shock & awe”, i.e. create a contrast with the norm People need proof What needs to change? Present the options Make THE suggestion How to achieve it What the results will be Outcomes
- 35. Aly Richards Content Audit/Gap Analysis Psychological Buying Journey SaleThreshold Advocate Content already created Content Gap
- 36. Aly Richards Editorial Production Planning • Briefs from maps populate an editorial calendar • Send briefs to content creators and manage through a workflow process
- 37. Aly Richards Psychological Buying Journey Above The Line Below The Line SaleThreshold Broadcast Advertising Social Media Social Adverts Website Adverts SEO Email DM Targeted Advertising Website (sales) Events Campaign Automation Sales email Call Centre Call Centre Next-Best-Action Sales Calls Cross/Up Selling Retention Bills On-boarding Comms Promotions Loyalty Call Centre Advocate Connect - Integration You can connect above the line and below the line activity in one seamless journey for the customer.
- 38. Aly Richards Psychological Buying Journey Action Interaction SaleThreshold Undertake research Find/receive relevant content Debating commitment Advocate Publish - Audience Experience Buying process Potential for advocacy Repeat or new purchase Have need Guided through structured journey & only contact is with relevant content Context of journey retained whether online or offline engagement Ongoing customer comms relates to buying intent Relationship sustained to find relevant cross-sell/up- sell/retention opportunities Experience & assess product or service
- 39. Aly Richards When & How?
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- 43. Aly Richards Performance Recommendations for analytics and insight gathering • Spotting opportunities • Measuring the entire journey • Connection to sales Dashboard design for BAU Go-no-go rollout from pilot results.
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Editor's Notes
- The future for online retail brands is almost certainly going to be refinements of this type of business model. For brands with brick-and-mortar stores keen to consolidate their offline-online shopping experiences, similar models will play a key part–if they aren’t already. If Very provides a snapshot of how future online retail looks, brands with a one-size-fits-all landing page, or even a three-sizes-should-do-it attitude, need to think again. Why? Because the individual is here to stay, they want what they want when they want it, and brands that provide the best personal service across multiple touch points are the ones that will win them over.
- Profile and profit What’s interesting about this is it shows that brands that take a more taxonomic approach to their customers, as in their opinions, choices and tagged preferences, increase sales almost by default. Dynamic personalization such as this, that helps customers make informed purchasing decisions, is fast becoming the digital equivalent of having a knowledgeable, real life salesperson advising on products. The beauty is, the advice is customer generated because as people browse and buy, good systems will learn and deliver recommendations with ever-greater accuracy. Additionally, the information they provide doesn’t leave the building with the sales people.
- Rules Generally ‘If, then, else’ test type statements that will guide a process. The tests are generally against statistic attributes or can be responses to questions. There is no insight and therefore little flexibility in managing a conversation. Useful for processes were the outcomes are of a fixed nature. Predictions Statistical predictive models built by looking at trends in data to find patterns. The model is then a mathematical formulae that customer data can be applied to in order to give a score or a prediction of how likely a customer will exhibit a behaviour. The models can be applied to targeting for example, within campaign selections. Campaign tools can generally only use one model for a particular selection. Predictions are used by both real-time marketing and real-time decisioning in different ways. Real-time Marketing Applying models and creating a campaign that is not executed outbound, it sits and waits for the customer to turn up and then is presented to the customer on the inbound. It is not context sensitive meaning that it is not optimized to what the customer just said. It is broadcasting on a one-to-one basis! The real-time part is that it is presented in real-time, but there is no processing done in real-time. It should be noted, that this will produce reasonable results for a lot of organizations. Real-time Decisions Models are scored in real-time when the customer interacts (any channel). Multiple models can be ‘fired’ and matrixed together with business rules in order to be reactive to the customers responses. A bi-directional negotiation is possible allowing for bundling and deals to occur that are specific to the customer. Optimization Generally applied to campaign management, allows the campaign manager to optimize which campaigns a customer would receive based on the optimization that they specify. This could be the budget that they have, response rate or revenue for example. Management Support Tools These are tools that provide support for management to make better business decisions, things such as scenario planning for media spend. They don’t affect the one-to-one interactions with customers. As such they are used more for efficiency purposes as opposed to revenue generation.
- Get to know your customers with research – surveys, focus groups.
- The Kid : Samantha, Aged 10. “Mummy can I join Greenpeace?” Goal: To satisfy her passion for animals and the natural world. General Visitor: Tracey, Aged 36. Mum. “I need some peace… stop fighting you two!” Goal: To keep the kids quiet for a couple of hours. Teacher: Colin, Age 43. “This time it will run like clockwork… it had better”. Goal: To prove he is capable of doing school trips. Nature Enthusiast: Neil, Aged 38. “No, no listen, this is really interesting”. Goal: To feed is knowledge.
- The next step is Customer Solutions. Now that you know your customer better you can shape your product to be a specific proposition for this customer.
- This template will help you think through what messaging you need to convince a particular customer to buy your product or service.
- For the purpose of this exercise we are only going to work on act 1. Consider what the customer is experiencing, what content do they need to move forward? Where will you offer variation of the journey and personalise it for your customer?
- You can cut what you are currently spending on traditional marketing by up to 50% whilst generating 3 times as many prospective customers.
- Rules Generally ‘If, then, else’ test type statements that will guide a process. The tests are generally against statistic attributes or can be responses to questions. There is no insight and therefore little flexibility in managing a conversation. Useful for processes were the outcomes are of a fixed nature. Predictions Statistical predictive models built by looking at trends in data to find patterns. The model is then a mathematical formulae that customer data can be applied to in order to give a score or a prediction of how likely a customer will exhibit a behaviour. The models can be applied to targeting for example, within campaign selections. Campaign tools can generally only use one model for a particular selection. Predictions are used by both real-time marketing and real-time decisioning in different ways. Real-time Marketing Applying models and creating a campaign that is not executed outbound, it sits and waits for the customer to turn up and then is presented to the customer on the inbound. It is not context sensitive meaning that it is not optimized to what the customer just said. It is broadcasting on a one-to-one basis! The real-time part is that it is presented in real-time, but there is no processing done in real-time. It should be noted, that this will produce reasonable results for a lot of organizations. Real-time Decisions Models are scored in real-time when the customer interacts (any channel). Multiple models can be ‘fired’ and matrixed together with business rules in order to be reactive to the customers responses. A bi-directional negotiation is possible allowing for bundling and deals to occur that are specific to the customer. Optimization Generally applied to campaign management, allows the campaign manager to optimize which campaigns a customer would receive based on the optimization that they specify. This could be the budget that they have, response rate or revenue for example. Management Support Tools These are tools that provide support for management to make better business decisions, things such as scenario planning for media spend. They don’t affect the one-to-one interactions with customers. As such they are used more for efficiency purposes as opposed to revenue generation.