Lose the Crystall Ball - FOM Jam slides
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Flick through our slides from Festival of Marketing to discover how to take the guesswork out of Predictive Analytics.
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Lose the Crystall Ball - FOM Jam slides
- 1. Lose the Crystal Ball Predict your customer’s next move
- 2. Grow Customer Value . Acquire More Than We Churn Create Brand Loyalty 2
- 3. The Marketer’s Toolkit . Automation PersonalisationSegmentation Predictive DRIVE 18 TIMES MORE REVENUE USING SEGMENTATION OUT-SELL COMPETITORS BY 30% - USING PERSONALISATION Source: eConsultancy, Forbes 3
- 4. “Making sense of large datasets is AI’s strength” 4 e-marketing
- 5. “The ability to use algorithms to automatically determine the likelihood that something will happen in the future, for instance likelihood to make a purchase.” Predictive marketers are 1.8 times more likely to consistently exceed shared organizational goals (Forbes, 2018)
- 6. Innovation Trigger Peak of Inflated Expectations Source: Gartner Trough of Disillusionment Slope of Enlightenment Plateau of Productivity Time Expectations Mobile BI Social Analytics Mobile App Analytics Predictive Analytics Real-time Analytics Conversational Chatbots Artificial General Intelligence Key Less than 2 years 2 to 5 years 5 to 10 years More than 10 years 89% of marketers have predictive analytics on their roadmap for 2016. (Forbes, 2016) 93% of consumer-facing businesses are unable to use predictive analytics (SAP, 2018) State of Disillusion… Does the market even know?
- 7. Single to Multi-Buyer Predicting VIP’s Customer Churn Allow marketers to accurately predict and influence lifetime value Prospect Conversion Predicting Customer Lifetime Value 7
- 8. Customer Lifecycle Approach . Lets look at getting predictive working within your customer lifecycle Predictive Automation Personalisation Segmentation
- 9. Acquisition Reactivation - Welcome Program - Registered Not Purchased - Abandon Category - Abandon Product - Abandon Search - Abandon Basket - Abandon Checkout - Back in Stock - Replenishment Campaign - Post - purchase campaign - First to second purchase - VIP Series - Anniversary - Birthday - Multi – purchase Campaign - Lapsing and Lapsed Typical Customer Lifecycle
- 10. 25-30% 10 Online revenue should be generated from your automated campaigns
- 11. - Welcome Program - Registered Not Purchased - Abandon Category - Abandon Product - Abandon Search - Abandon Basket - Abandon Checkout - Back in Stock - Replenishment Campaign - Post - purchase campaign - First to second purchase - VIP Series - Anniversary - Birthday - Multi – purchase Campaign - Lapsing and Lapsed
- 12. 12 Prospect Conversion Campaign Put an automated series in place to target customers they have signed up Use the typical time lag between signing up to the brand and making a first purchase 12 Talking to your customers: Why purchase with our brand? Personalise with content they are interested in Channels
- 13. Limitations Not sure which customers are going to purchase Therefore not sure of what content to send them Inefficient channel spend Using Predictive Technology Vary content based on a customer with a high or low propensity Improve spend efficiency and resources Send them content that is relevant to them
- 14. High Likelihood to Convert In Next 30 Days Low Likelihood to Convert In Next 30 Days USP and brand Automated channels with lower spend and inspire purchase Offer and incentive driven More channels to convert 1414
- 15. Converting Prospect Customers High Likelihood to Convert In Next 30 Days Low Likelihood to Convert In Next 30 Days Create audience exclusion for paid social (Google Match) and search adverts (Custom Audience) Get Inspired this fall. Inspiration content with heavily focus on customer testimonials, delivery and returns Time sensitive offer email supported with count down clock Personalised Site Banner: Promote offer or reinforce delivery or returns option to increase likelihood of purchase Social extract: Facebook or Instagram advert. New customer offer this weekend only Follow up email campaign with closing sale message. SMS used to support non openers of first or final campaign. Interactive email with social scrape of latest Instagram content to promote purchase from trending content Customers Scored By Model Final email with new ranges just for you – Recommend content 1515
- 16. Predictive Prospect Conversion Predictive Modelling Retaining new and disengaged customers to secure their LTV While increasing top-line revenue CONVERSION INCREASED BY 27% 16 03 05 47 58 03 05 47 58 YOUR CODE: 10OFF-AUT
- 17. 17 Acquire More Then We Churn Create Brand LoyaltyGrow Customer Value How Do You Measure Success? . • What is the uplift in VIP customers? • Control test • Have re-reduced our overall customer churn? • Have we reduced the cost to acquire a customer? • Have we created increased lifetime value across our database?
- 18. Acquisition Reactivation 83%Increase in second purchases 66%Increase in VIP purchases 54%Reduction in churn 18 27%Increase in first purchases 34%increase in LTV 18
Editor's Notes
- Hi I’m Roisin form RedEye We help brands increase their customer LTV with AI driven database technology Just to be clear I am not sales person - I am not going to sell you on what predictive Also I am not an analysts - I am not going to talk to weather the models are built on R or Python What I do is help brands intrepid their data and what want to do is talk through the common questions I get asked How to use predictive When to use predictive And how to measure success Be Practical – Not what it is I am not a sales person I work with brands everyday to implement the right solution for them objectives. How to use Predictive When to prioritise it How to Measure success
- Lets bring it back you and what you are trying to achieve? In my experience regardless of industry sector it boils down to: - acquire the right customer, and ensure we retain more then we churn - give rich customer experience – to grow value - and we wan to build a loyal customer base
- We all know that key driver for success is data But for once I am not talking about building that SVC and what are the richest dataset We are focusing on the accessibility and actionability of that data Key areas we focus on to optimise the customer experience is - Automation - Segmentation - drive 18 time more revenue - Personalisation - out sell competitors by 30% These have been the bread and butter for years and evolved over time. Now we are throwing predictive analytics into the mix!! The questions I get asked is: How do I use this? A common theme I find when it come to planning to use predictive we try and overly complicate already complex solution. This is not surprising for years we have had to hand pull data form multiple sources, overly an analytics tool, try and drive insights form this and drive this into a creative marketing plan
- My recommendation is “Let the product do what it is designed to do”
- We need to stop trying to control everything. I will hold my hands up I can be an control freak – I was on honeymoon just last week and I was checking work email every chance I could. I am sure you can imagine how well that was down. We need to trust the algorithms, they are taking into consideration 100’s of thousand customer touch points to determine the what the customer will do next Not sure did anyone get the chance to see our CCO’s presentation this morning? Basically we are now at the point where we can confidently sat these work I hold my hand ups I was shocked by the results - we are reducing customer churn by 54%, increasing LTV by 34%
- I don’t know about you guys but I am bit of geek I love reading about our technology and data what happening. I am sure everyone has seen the Top Trends in the Gartner Hype cycle – about emerging technology Its we don’t start trusting the data and making this real risk in another 2 years we will be conflicting on what we had planned to do.
- There are lots of different predictive models in the market . . . But we have looked at the foundation of the marketing strategy improve performance at each stage of the customer lifecycle with the overall goal of improving customer value!
- Our approach is not about using this as a separate identity but use presitive to drive what you are currently to maximise the value of your marketing mix.
- This is a typical customer lifecycle, were we are drive customer through the different stages. Some brands have a top 11 campaigns live, some have over 400 targeting customer as they move through stage.
- Let not under estimate the value this can bring. Brands see 25-30 online being generating form these automation comms
- But there is still revenue opportunity that we can start to take advantage of. We have 6 Models 5 – enable to improve and drive actions 1 – allows us to calculate LTV and predictive what your LTV will be in 12 months for frocasting. Don’t worry I am only looking at 1 today. Driving your prospects to make their first purchase. Why We spend so much time and effort acquiring these visitors To end up with 44% of the overall database who have never purchased There is so much opportunity for you as a brand.
- What are you currently doing to convert prospects Running analysis to see the lag time Then applying this into an automated series You should be able to talk to them based on what they are interested Typically we see brands use 6 channels at this stage
- We are already doing a lot to convert these customer what are out limitations. WE don’t know who is likely to purchase There not spending right channels Not commutating with the relevant message By apply predictive this should reduce this risk within your targeting approach.
- What happens: - algorithms look at 1000’s of variable - Scoring prospects - Automatically builds threshold - based on your seasonal trends, customers buying habits - Define the time frame you have to convert - create a persona of those customer so you know what to say to them.
- So we have our segment We have the information about the customer We know what your objective is Now we just use it. At this point I would always let your prospects go through your welcome and conversion campaigns then use predictive to drive additional revenue. High - BAU - they are going to convert use that segment as an exclusion to manage spend in your paid activity. - Can we inspire to spend more by scraping through Instagram content on key trends Low - your are probability asking yourself why bother - if we can convert an additional 10% what would this mean to your brand. - use your key marketing message creating urgency, if appreciate try incentivicing these people instead of everyone on the database, maximise your channel reach.
- Most important thing I would say is TEST. Measure these against a control cell. When we don’t this for footasylm we seen increase against the control of 27%
- Renton rate LTV Control
- If I can leave you with points: It does not need to be complicated – let the Modelling do what it is designed to do Test what works – model give you what you need to miked decisions – perfect blend between technology and human interations Use LTV are Key KPI Measure against control cells.