Lose the Cookie!

If you missed our fireside chat with Adobe, discussing everything First-Party and Third-Party data related and the opportunities that exist in real-time personalisation – we invite you to catch up here.

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Station10 Fireside Chat: Lose the Cookie, gain real time personalisation. Summary notes from session 7 July 11am:

Hosts

• Steve Allison, Senior Manager, Strategic Marketing EMEA, Audience & Data Technologies, Adobe 
• David Ellis, Managing Director, Station10 

Scene setting/context  

• There has been a lot of discussion about data deprecation and that is going to affect marketing campaigns and media advertising less discussion about customer optimisation and customer personalisation
• Real time personalisation is one of the biggest topics for 2021 and beyond
• Yet so far, the focus of conversation has been about the death of the cookie, the downsides 
• Focus on the opportunities we can derive from First-Party data and trend towards data permissions, 
• Also an opportunity to understand it is blend of people, process and technology and we want to understand what we can do about it   

Update on Cookies

• The latest focus on Google Chrome will be deprecating 3^rd party cookies from the end of January 2022 is now extended towards the end of 2023
• It’s a time to reflect on regulation and consider the challenge of how FLoC there proposed solution lock maybe struggling to demonstrate its potential value
• There’s more time to make strategic decisions about what is happening
• 3^rd party cookies do not respect privacy and consent and that needs to change
• What that change is going to be not resolved
• Need an open way to address it and come up with independent solutions to mitigate these privacy issues
• The main sacrifice when we go 3^rd party Cookieless is cross domain tracking, there is no real soliton to that
• There are independent solitons that can mitigate that 

The direction of travel

• There was a narrative that it may get reversed, but it won’t happen because it is driven by other factors
• Apple is making a big deal about privacy and stopping/disabling tracking, unless you need it be there, the transparency in tracking may be dictated by Apple
• If Apple and mobile phone vendors are making this about a point about brand positioning in the future, then things are going to change  
• It’s been a development over the last year or so

Opportunities for change

• Data collection strategy across the business is now fundamentally changing 
• It is an exciting time, allows us to reframe our mindset:
  • How do we get customers to allow their consent and permission?
  • What is the deal about value exchange?
• Previously there was a sense of entitlement to use cookies by digital marketers
• There is an opportunity for brands to change their mindset with customers
  • How can retailers build trust with their customers?
  • How can we move towards people doing proper personalisation?
  • How can brands properly develop their brands?
  • How can people based analytics reframe how we understand that person? (it’s about people 

Impact of personalisation 

• People still want a personalised relationship or experience, it is a clear benefit
• There is a difference about how value exchange, why should they exchange data with you?
  • Personalisation is one part of that there must be a whole exchange 
• This is not just a data or marketing question it is bigger than that 
• There is a requirement for broader engagement that requires much more of customers in the discussion
• Must continue to procced with relevancy whatever the engagement to start proper personalisation if you can persuade them to part with their data

Considerations for personalisation

What data do I need? This is the first question we should ask.

• We need a different level of personalisation – we can’t treat everyone the same
• If just getting to know them need to understand those metrics before you move them on
• Early on consider how can we encourage data sharing? 
• Recognise there will be a lot more anonymous people
• Need much more contextual relevancy or anonymous personalisation through machine learning to off balance if they are anonymous and if you want to get to know them

Opportunities for personalisation 

• We need to change the mindset how we see the customer over the longer term, (it’s not about a single interaction
  • How can you understand that whole customer journey?
  • How can you understand the multichannel journey or instore?
  • How can we consider the longer-term view?
• We must consider the customer in terms of life-time value as a key metric
• At Adobe it’s all about ‘creating experiences’ at any point in time you must get personalisation right, right time, right content 
• The experience comes from that multi-channel approach, a single conversation across them all  
• We must get the person right across all the different channels 
• We must get the ‘right here, right now’ then build that experience 
• With streaming data we can start building that one profile and understand them over time 
• There is a move to coalesce data, have a consistent approach which can build the relationships and drive data over the future

What can we do to start to do about it?

• It’s not all about technology
• If Cookies are disappearing, do we need to move server side? (what is the approach behind that)
• It is 3^rd party cookies that are being deleted, this means the 1^st party cookies on server side, there are viable ways to still do things  
• Should we be just moving to streaming based data collection that gives much better potential benefits?
• How can we change that data into people a person’? (it’s useful data)
• Where does identity services and profiles come into the mix?
• How do we move from a DMP (data managed platform) to a CDP (customer data platform)? 
• This starts in marketing to rationalise this down to people  

How do we get breadth across the organisation?

• It is no longer a digital marketing or ecommerce conversation; it is much broader than that, it has been for the last few years 
• It’s a conversation much broader than this, with compliance and legal to talk about cookies and value exchange 
• We need to get that buy in, this is a business critical conversation  
  • Consider how you do you want to be as a business?
  • How are you communicating what you want to do with the data?
  • Are you capturing what you say you are going to capture?
  • Are you going to use it in the way you are going to use it?
• You have to tell people across the organisation about what you are doing
• People and process must be built in and think broader beyond the behavioural data

How can we do more?

• Run surveys, link that to the data, to enrich or augment the data that you have 
• Ask customers at different levels, gives you more to work with to get them to the next stage
• Consider zero party data – what are you asking them to tell them about themselves?
• 1^st party data is more about observing the data
• Need to really think what I need the data for?
• Businesses/partners need to work together better to initiate proper planning to serve the business end

Growth in 2^nd party data 

• It’s another key growth area
• It’s about someone else’s (1^st party) data that they are legitimately sharing with you
• How can you augment this data? Share it through a clean room and join some key attributes from both  
• Then bring it back in house

Example

• Strava fitness app offers, set a Strava challenge, if run 10 miles a month get a partnership offer/discount, condition is that you must share their data to get the offer
• Having a new specific relationship with publishers, advertisers, and partners 

• It works with B2C and B2B, 2^nd party data is going to be huge
• The olden days of buying audiences 3^rd party are gone, the 360 view of the customer 
• It’s about sharing that data, following consent, using declared identity can go a long way
• This is a segment match or data clean rooms are doing the same thing bringing information together
• Partner data share has a huge impact on the audience expansion 

Example

• if I was buying a new car and the data matched it could be that I was expecting a new baby, then business partners could respond to that combined data for a combined goal 

• A lot of the challenges is about removing the politics about sharing data internally
• It’s about how to personalise internally we use case by case data to get buy in to address the challenges

Important to have a change in mindset

• Winning consistently over a long period is important, who will be first and fastest 
• London School of Economics and  Adobe published a ‘New Era in Experience Report’ to signpost how by making the most of data
• People who make the most of their strategy (interdepartmental teams) who bring together data together are customer centric and this has led to a resurgence in the interest in customer journeys
• If you have streaming information, you can use that event to drive to further nudge points or touchpoints which starts to build a customer relationship
• It fulfils the users need for immediacy and relevancy for the customer and we can start to build that relationship to create a win/win situation 

Does this mean can’t personalise as well as we used to be able to do?

• There is a difference between personalisation, experience and targeting 
• Personalisation is about getting to know them through data
• How are you targeting people that you don’t know? (machine learning has a huge part to play)
• How does machine learning help to predict what are they going to next?
• Need to ensure the data is useable to build an experience over time about those people, feed off the information 
• Machine learning and data science helps at each stage
• 1^st stage: don’t know the customer very well, that where the cookie has been the most valuable 
• Machine leaning allows to learn about what we do have 
• Applying data allows us to bring about internal lookalikes to understand how who we have just got in, machine learning models are the key difference 
• Personalisation is better than it ever has been before
• GDPR and cookie deprecation is clearing away the fog that we thought was necessary
• Machine learning can analyse customer journeys, it can be really fast and can help people realise the value of giving data far earlier in their user journey, what is working, what is not
• It compresses the user journey into a positive step  
• Machine learning is going to be a vital part of everyone’s toolkit moving forward
• B2B are thinking about this and it is not sector specific 
• B2B is tending to copy some of the B2C techniques, it is all about having a relationship with people, bring the techniques, it’s about   
  • Who are you, where are you in the process?
  • Collect and store the date as a profile
  • Leverage that data in context as a person, a household
  • Build combined intelligence if you have the data timely enough

Summary key points/tips  

• What is the approach, where do we start?
• There are three streams to understand, technology people and process.

People and process

Start to kick off two streams, follow these steps 

1. Start a value exchange discussion 

• Why should people/customers share information with our company?
• It requires a mindset shift; how can we share customer information within
• Encourage a shift towards long-term business value
• Those companies that are using data in the right way will be the real winners over the next 3-5 years

1. Mapping data flows

• Where are those flows going? 
• Consider how exposed you are to 3^rd party risk?
• Where is the organisation being the data being used?
• Who are my stakeholders? (to educate, take on a journey)
• Start those discussions to take people on board internally

Technology

Two things to look at 

1. Move to streaming 1^st party people based data

• Make sure your strategy is giving you this 

1. Start looking at CDP type user cases 

• How can you bring that data back as a profile 
• Co-ordinate real time data sets to move towards personalisation
• Start to collect that profile data to build better personalisation and better profiles into creating better experiences

Beginning of a journey 

• These methods can be put in place, it is happening now
• This is happening now, it is the beginning of a journey
• A journey of data to drive transformation, it is not blue sky thinking
• We have breathing space to get the internal planning sorted 

Future – 3 years’ time

• Consider where you want to be if you fast forward
• Consumers will be savvier, and they will value relationships 
• They want to be valued and be treated in the right way
• Those who the best data ethics will get better long-term brand value
• Some will say they don’t need that data and they won’t use it 
• Brands will start to step up to use a case-by-case step by step 
• Refine data as you go along to determine what will make the most difference 
• Create a collection of internal case studies
  • To create long-term buy in and interest internally 
  • To create a momentum for the future programme
  • To create a centre of excellence within the organisation  

NEXT STEPS:
Arrange a free and confidential discussion with Station10 and Adobe on your current plans towards your First-Party Data Strategy and what steps your business needs to take.