Future of Cookies: Contents
Future of Cookies – Part 1: Introduction
The future of Cookies is an issue that is worrying advertisers, publishers, managers, business owners and pretty much anyone else who uses digital advertising for their business. A lot has been discussed about cookie deprecation, and in particular increasing awareness that third-party cookies are going away and likely won’t be coming back. Throw in IOS updates that gives people the option to opt-in to, and therefore the option to opt-out of, tracking on third-party sites and it’s clear that the limitations of cookies (well third-party anyway) are being exposed.
This is far from a bad thing, as whilst all of the above are making digital advertisers have to re-think their strategies, the new approaches required lend themselves to what consumers are increasingly after. The expectation of personalisation, the increased awareness to see action around privacy concerns and the requirement of customer centricity means that, whilst reacting to certain doors being shut, we can create experiences more closely aligned to what consumers want.
On top of this, the change in tack required to deal with the increased limitations of cookies has internal benefits to organisations as well. A move away from third-party cookies towards zero and first-party data will do great things for improving the accuracy of data within organisations and breaking down internal silos.
All things considered, third-party cookie deprecation is not something to be afraid of, in fact, it provides the perfect stimulus for companies to re-orientate their processes, become more customer-centric, provide better experiences and improve internal communication and collaboration.
Here at Cake Mix HQ we’ve been evaluating what these changes mean and the first and zero-party data customer journeys you can create in response to them. The results are really exciting and allow you to engage customers on their terms, in a targeted and effective manner.
We’re going to introduce you to our ideas, our research and the discussions where we map out exactly how to make the most of tools at your disposal. (Most of which are completely free to use) This area is ever-evolving and we want to take you on the journey with us to understanding the future of cookies, how to use first-party data, how to get zero-party data and how to pull it all together to create brilliant experiences for your customers.
First things first let’s get our terminology straight about the different data flavours.
You can see a video of Ben explaining these here.
Future of Cookies – Part 2: Getting started, Success on a slim stack
You might be looking at this and thinking to yourself “So third-party cookies are going away, but what do I do about this?” and it’s not only a fair but pertinent question.
Facebook and Google, two companies whose ads are definitely affected by Cookie deprecation and IOS updates, are simultaneously trying to assure advertisers that everything will be absolutely fine, and you can still target consumers effectively, whilst also assuring consumers that they care about their privacy and won’t allow them to be targeted in the same fashion as before.
Obviously, this is not a knife edge they can balance on for ever.
The common consensus is that you will still be able to target consumers, though not as effectively. Some of the ad mechanisms and processes expected to take the biggest hits are:
- Multi-touch Attribution
- Ad Analytics data
The long and the short of it is, you will probably spend more, get fewer conversions and have less oversight on what’s happening but still ultimately will be able to advertise using many of the tactics you did before – but if you do that the competition will be leaving you behind as they start to harness the power of first and zero party data.
There’s a host of articles out there explaining all the damage the limitations of Cookies will cause so we won’t labour the point too much here. Our focus is less on the hand-wringing “How terrible it all is” and more on the “Here’s how to still get stuff done”
So let’s get to it:
Now there’s a host of expensive and slightly less expensive customer data platforms, customer experience platforms and other tools which do admittedly, make cookies deprecation easier to deal with. But you can get a great deal done with your website (and CMS), CRM, Google analytics and Google ads – you’ll either already have these (website, CMS & CRM) or can get them for free (Google Analytics and Google Ads). Using this simple stack and the right strategy you can easily deal with third-party cookies going away.
An important aspect to consider with your stack is how well the elements integrate with each other, most modern platforms are pretty good at this but evaluate them now because otherwise you’ll be in for a heap of frustration as we start to progress. Many have built-in integrations, others allow you to use tools such as Zapier to connect them. Do be wary with this, as whilst Zapier is a great tool it can’t start to run costs up based on the number of “tasks” it’s having to fire.
Your CRM will be key to your new strategy, this is where a lot of the magic happens when it comes to using zero and first-party data. Most modern CRMs have the required bells and whistles to bring your data recipes to life but if not, we can highly recommend Hubspot, yes we are a Hubspot Diamond Partner – but all bias aside it really is a great platform for what you’ll need to do in terms of segmentation.
Which brings us nicely onto something that is critical to the success of your cookie deprecation plan – segmentation and personalisation. We’re going to do a thorough examination of segmentation and personalisation but it’s important when looking at your tech stack to examine how wide ranging your segmentation and personalisation options are because these will be crucial to your success.
This will lean heavily on your CRM and web CMS. Most CRMs will allow you to create numerous persona segments based on the first and zero-party data you feed into it and the really good ones will allow you to use that information to start shaping the personalised journeys for your visitors.
The next step is to use the information around your personas to create personalised experiences by using tools like dynamic content. Most CMSs have this as an inbuilt option or as a plugin and the majority will allow you to create these experiences via a direct connection to your CRM. For others it will be a case of deciding what the personalisation trigger for each group is and manually setting that in your CMS. This is a far less elegant solution so ideally you want to make sure your tech-stack has a modern CRM and CMS that will allow the integration.
If yours doesn’t then you should consider finding a new one, not simply because it won’t allow you to deliver on this strategy, but it suggests the company behind them is not innovating enough or even following trends enough to give you the value that needed from a CRM and CMS.
So you’ve got a CMS and CRM that will integrate with each other and allow you to segment and provide personalisation, next up, its key to integrate Google Analytics (G.A.) into this stack. G.A. won’t just provide you within insight into how people are behaving on your site it will allow you to feed that information back into your CRM to keep building your personas and gain a richer, fuller experience of how users are behaving on your site, how they are engaging with your personalisation and where the key drop offs are.
The other advantage to having a well-integrated analytics and CRM set-up is when we bring Google Ads into play, as you can automatically add them into remarketing lists in analytics which connects to Google Ads allowing you to retarget your web visitors. Now I hear you say: “but Cake Mix, you told us what with third-party cookies going away that remarketing would be affected”. Now this is certainly true but there’s a few caveats to that.
1 – RLSA – or Remarketing Lists for Search Ads to give them their full title. Word on the street is these will be unaffected by Cookie deprecation as these rely on Google’s Cookie and a search query on Google.
2– As mentioned, Google relies a lot on advertising (in fact it’s the main source of its revenue) so they’re not going to kill the golden goose completely, its already got replacement processes in the works and you will still be able to remarket on Google owned and operated media but you won’t be targeting individual users and instead will target cohorts.
Any who this is meant to be about how to use first-party data and how to use zero-party data which means we don’t need to get too bogged down in what third-party style features will still be available.
If you’ve got Google Ads integrated with Google Analytics you will be able to create lists based around your personas and target ads based on audiences that look similar to them or target them, based on their email. This works on other platforms such as Facebook and Pintrest as well. This means you can increase the LTV of your existing customers and target other consumers who would fit well with a particular segment and the messaging that resonates with them.
So that’s what required for your nice, lean integrated stack. With a good CRM, CMS, Google Analytics and Google Ads you’ll be able set up a host of great, personalised journeys targeting the right person, with the right message at the right time.
– Unsure if your stack is up to it? Then get in touch and we can help you evaluate it.
If you want some advice from Google on integrating analytics and your CRM then head here.
Future of Cookies – Part 3: Segmentation & Personas: It’s not what you know, it’s who you know.
As we’ve already alluded to in this article, segmentation is absolutely critical to the Data Recipes approach to surviving the future of Cookies. It’s vital across most modern marketing to be honest and if you’re not doing it already, then now’s a great time to start. Segmentation allows you to mean more to your customers by delivering the right message to them, in the right format, on the right channel at the right time.
We will do a thorough unpacking of how to segment you customers within your CRM, not just from a strategic point but a practical hands-on guide. But a key part of that that needs to be addressed in tandem, if not first. And that is one of the most important marketing questions out there “Who am I selling to?”
Because this is how you start segment your customer base and to create personas. Personas and segments are often used interchangeably but they are different – a key differentiator is that segments are mutually exclusive and personas don’t have to be. Segments are high level categories whilst personas are individual archetypes. Confused? Well I’ll give you another one – personas are great for understanding the motivations of your customers and segments are great for targeting specific groups and measuring the impact your marketing has one them.
Segmentation is crucial to modern marketing. Mass-marketed, generic messaging has less and less place in today’s society. Personas allow you to go beyond looking at your customers in terms of demographics, location or device users and instead see them as real people with likes, dislikes, affinities, brand preferences, nicknames, catchphrases they like and celebrities they aspire to be. By viewing your customers in this way, as real people, you can craft communications that truly resonate with them, and reap the commercial benefits that come with this.
With third party cookies going away, being able to rely on your view of your customers and the addressable market, rather than relying on the information third-party platforms amass, is crucial.
But what if I’m a start-up and I don’t have any customers or first party data? That’s cool – we’ve all been there. We’re going to have a whole section on the future of Cookies for those just starting out, but for now you’ll have to create proto-personas based solely on assumptions and research and validate them as you gather customer data. Once you gather this data you can start segmenting those in your customer base.
So how do I get started?
This is where first and zero-party data comes into play. The data you have on your consumers from their interactions with your company, what they buy, the device they use, the content they engage with, their email open rates, their order value, their frequency of purchases, their location, their…well we could be here for a while. But any of that first-party data you have collected is a great resource to start segmenting your customers and creating personas.
You can add to this with zero-party data that you have explicitly exchanged with your customers. We’ll go into a full break down of how to capture zero-party data but you’ll often be using a survey, quiz or questionnaire (with explicit value in return for the user). The great thing about this approach is you will be designing the mechanism yourself, that means you can form your questions around the traits you want to shape your segments & personas round.
Say you’re in the travel industry, you’ll have some customers who plan everything a year in advance (Early Birds), some who do it a few months before (Middle Roaders) and those who do it a few weeks or days before hand (Last Minuters). All three of these segments will warrant different messaging and timing, so would be a good basis to start forming your personas (though ultimately you want to divide these personas even further) You would want to have the first-party data to understand how far in advance of their holiday they booked but you could use a survey to ask questions about why they booked when they did.
The “Why” is one of the most important things you can understand in marketing. “What” your customers do is all there in your analytics data (first-party) but the “Why” – that’s the crucial bit. That’s where you understand your customer’s needs and wants and all the motivators that show you why they chose you, why your messaging resonated, why they chose to buy, when they did and why they chose you over the competition. This is all available as zero-party data and will allow you to build personas based around customers’ motivations, not just observed data about how they behave.
So back to our travel company example, asking your customers “Why did you book your holiday when you did?” will provide you with great information to start profiling personas. You could use your first-party data to provide different surveys based on when they book. So, your Early Birds, Middle Roaders and Last Minuters would all get slightly different surveys and answer options. If you’ve already got some idea behind their motivations, you can provide answer suggestions which differ depending on whether they’re Early Birders etc. The “Why did you book your holiday when you did?” answer for Early Birds could be: good price, peace of mind, range of options, and an “other” section which, if popular enough, will allow you define another persona creation point. For Last Minuters the answers could be (spontaneous excitement, money spare at the end of the month, last minute deals).
You can then start to build your personas around these areas: Early birds who like a good price and Early Birds who like the peace of mind of getting it sorted all the way to Last Minuters who like the thrill of a spontaneous trip and everything in between.
With an understanding of their “why” you can create bespoke journeys for each persona with messaging that really resonates – and you can see why from the examples above. The Early Birds who like peace of mind are not going to engage as readily with messaging for spontaneous Last Minuters. We’ll come onto how to create great personalised journeys later as that’s a whole awesome thing unto itself.
An important note when collecting your zero-party data is to make sure you are asking why people did something rather than what would they do. People’s opinion of what they would do and what they actually did are dramatically different.
You can see from above how you can start profiling your customers with first and zero-party data now to start bringing you personas to life. You can use the key points, like the ones around the purchase to consuming period and the “why” to create you’re the skeleton, but now you need to add some flesh onto this.
For this look for other trends across these groups. Separate them all out into lists in your CRM and see what other zero and first-party data trends you can see within the groups. Do most of your “Early Bird – Peace of Mind” personas use your deposit and payment plan option? Then great, that’s another attribute. Do they also primarily engage with your content on Facebook? Great, there’s another one. You can supplement this data with research. The internet is full of great consumer trends, full reports from the likes of Mintel and Euromonitor are available but can be pricey, but with some good Googleing and some demo downloads you grab some useful snippets here and there which will help add colour to your personas and bring them to life.
What’s in a name?
Speaking of which, it’s useful and far easier to give your personas names, this helps them become a real person in your mind and helps separate them in your head more easily. For example, Early Birds who like peace of mind could become “Patient, Peaceful Patricia”. Now alliterations come highly recommended for this task A) they’re fun B) it seems to be the standard C) they’re probably easier to remember but mainly point A.
Start to build the persona with demographic data, does their gender skew one way or the other, what’s their age range likely to be etc. If there’s commonality in geography then include that, and this doesn’t just mean one city or country, are they rural, urban, suburban, renters, home owners? A lot of this you will have exact data on, but you should always look at persona building as semi-fictionalised – for example what car do they drive, do they have a cat or dog, where do they like to shop, what other brands to they engage with. You will have some clues as to some of this but a lot is conjecture and again designed to help bring your personas to life, to make them real people and to help you understand how best to speak to them.
With segmentation and persona development you should never look at your work as “done”. You should constantly look to keep building, developing and adding your profiles as you go. One great way to do this is if you require a login to access your service, site or product. After every login you can ask a new question, all of which gets stored in your CRM and helps develop your segments and personas even further. This “Progressive Profiling” is a fantastic way to use zero-party data to keep adding colour to your buyer personas and build increasingly accurate pictures of who your customers are and what their needs, wants and motivations are. Personas and segmentation are crucial to creating the personalised journeys that consumers expect and that deliver the greatest commercial results.
With the host of first and zero-party data available to businesses now, the opportunity to create deep and rich profiles is huge. Creating these journeys starts with effective segmentation in your CRM, and your personas play a big part on shaping these segments. The great thing about starting with personas is you are dividing up your customer base by their “Why”, on their key motivations. This means when you are constructing segmented journeys you can do it on messaging, messaging designed to resonate specifically with that group. There’s a host of different techniques to segment with, that we’ll go into more details in the next section. Some of these you can do ahead of time, segmenting by CLTV for example, others you can do after campaigns, such as CHAID. We’ll go into a few of them, but for your personas, profiling by the “Why” means you’ll always be targeting a group based on their core motivation, and the best way to understand the “Why” is to speak to them. Gather that zero-party data and create a better digital experience for your customers, your team and your bottom line.
Future of Cookies –Part 4: Segmenting your CRM: Divide and Conquer
In the previous section we talked in length about creating profiles and personas to ensure you are creating messages that resonate effectively with your target audience. We chose to do that around the customer’s “why”, but there are a host of ways to do this, such as segmenting around LTV or around specific strategic objectives such as increasing the frequency of purchase of a particular group. With all of these different segmentation and profiling approaches the important thing is to make sure you are doing these for a commercial reason, that you have a firm objective and your activities all lead to that.
In this case the objective is profiling your audience to make the most of zero and first-party data before the deprecation of cookies leaves you in less than palatable creeks without appropriate propulsion. We’ve gone through profiling and segmentation processes and guidelines but now we’re going to look at how to implement this on a tactical level within your CRM; how to create segments based around the first and zero-party data you have, how to arrange these segments, the fields connected to them and how to ensure they’ll integrate smoothly with your outgoing messages to ensure your targeting the right people, with the right message, at the right time, on the right channel, with the right media.
We’ve already spoken about the need for some simple integrations between your ads, CRM, CMS, and Google Analytics. This is a cyclical relationship with information flowing from ads to CRM, to CMS, to analytics back into CRM and back into ads.
The CRM is the centre of this machine, it’s here that you will take you customer data and segment it. Then you can create personalised web experiences for each segment with your CMS. You can then connect to Google Analytics and ads to target your customers with ads or create look-a-like audiences to target, who themselves will come to your website and add to the first-party data profiles in your CRM. This will allow you to provide even more personalised experiences through your CRM.
This way you’re constantly adding to the segments in your CRM, but not just with numbers, with richness of data as well, with behaviours and learning, helping you understand your users and customers in greater detail, so you can provide even greater experiences. It’s a wonderful, virtuous circle with explicitly consented data at the heart of it.
Anyway, enough evangelising, lets get into it.
It all starts with the segments in your CRM. You’ve already looked at your data and created personas, now to separate your contacts out to match these personas. There’s a few ways of doing this but creating separate lists within in your CRM is a sensible starting point. There is a line of thought that suggests that a contact can belong to more than one segment, and whilst this is true, for delivering on the approach we’re outlining its best to limit your contacts to one segment. This means that when your communicating with them through ads, dynamic content or email that they are getting one clear message. It’s true that they may share attributes and preferences with contacts in other segments but we still want to keep them separated to ensure the messaging is spot on.
For the purposes of this blog I’m going to assume that your CRM isn’t segmented at all and is currently one long list of people all receiving the same message. So what you want to do is start segmenting them. There’s loads of ways to do this, you can do it by one variable: how much they’ve spent with you, by two: how much they’ve spent and how long they’ve been a customer. The more variables the more specific the messaging will be: If you’ve got two customers who’ve spent £10k with you but one’s been a customer for 5 years and one’s been a customer for 6 months, you’re going to want to treat them differently.
My preference is to do it by their motivation, their “why”, as this means your messaging will always be well targeted. Let’s carry on with our travel company personas:
We want to be dividing them up by the time between when they booked and when they traveled. Some CRMs will allow you to do this in platform, if not, it’s time to export to CSV and do it by hand. Export your contacts with those two fields. Then use Excel to tell you them time between purchases and travel. A range of 365 days to 0 days let’s say. Now all segments you ever create should be measurable, substantial, practical, identifiable, accessible, responsive and sustainable as to be worth targeting. So as we’ve got three distinct personas we’ll have to decide at where we put the segmenting point – where do Middle Roaders end and Early Birds begin?
Well if you’ve got 9000 customers on your database the earliest 3000 would be your Early Birds, the middle 3000 your Middle Roaders and your final 3000 your Last Minuters. Now it might be that 7000 of your customers booked within two weeks – which may prompt you to change how you’re segmenting, but for the purposes of this discussion. We’re going to assume a nice linear distribution and that our first 3000 can be found day 365 – to day 200, then next day 199 to day 75 and our last 3000 day 74 – 0. These are the basis for our initial segmentation.
Early Birds – People who book a holiday between 365 and 200 days before they travel
Middle Roaders – People who book a holiday between 199 and 75 days before they travel
Last Minuters – People who book a holiday between 74 and 0 days before they travel
We can put these into three separate lists, upload them to our CRM and apply tags or custom fields accordingly to be able to easily identify them and send them more personalised messaging.
You want to be able to update these in real time which means after you’ve segmented your customers and they book further holidays you can seamlessly move them from one segment to the next. This would involve using an internal CRM automation using a WHATIF function. The granularity of this will depend on the CRM you use but a WHATIF function around time between the two fields of “Booking date” and “Holiday date” being greater than X number of days should be able to automatically move contacts from one list to the next.
A great next step would be to survey (in exchange for something as ever!) your customers to start building richer profiles and develop more segments. So create those surveys and send them out to your customer groups. You could say to Early Birds “You like to book your holiday well in advance, why is that? Good price, Peace of mind, Range of options” And then divide the 3000 early birds up further by those categories and apply fields and tags accordingly and set in place automations to move people from one list to the next automatically.
Now you have a CRM segmented by behaviour and interest, with automated systems to move people from one segment to the next.
From here you can trial different messages to each of your personas and see what gets the best engagement and response. You can do this through email, SMS, dynamic web content, chatbot messaging, direct mail – what ever comms. channel you can think off. You may find different segments have channel preferences and different messaging preferences, so you can set up fields, tags, automations and workflows to make sure these are the ways you speak to them.
You can further enrich this by looking at other common attributes of your segments from your first-party data. Do your Early Bird Peace of Mind crowd also have the longest time on site? Do they have the highest email opening rate? Create a field in your CRM and add it as an attribute, this can help guide you. Add these in automatically with automations based on contact actions.
Remember with all of this what your goals are, yes mean more to customers, speak to them as they want to be spoken to but to get them to spend more and to spend more frequently, for as long as possible.
All your segmenting activities should be focused on achieving these outcomes. So great, you know one segment much prefers email to SMS in terms of response rate, and they prefer a message early in the week, in the morning, also great, and they respond best to messaging around the peace of mind that comes from knowing you don’t have to worry about booking your holiday. But the real magic is combining this all to influence behaviour to drive commercial outcomes.
One of the great things about segmented lists is that you don’t have to create them in your CRM, you can do this in Google Analytics and hook it up to your Ads account directly. This is more specifically for re-marketing which is obviously a fantastic tool for conversions but something that will be impacted by 3rd party cookie deprecation. This is definitely going to have an impact on display ad, though Google are doing the best the preserve this revenue stream by having everyone login to the platform, thus making their browsing information first party data. But one area that will remain untouched will be search ad retargeting due it all being contained within Google search and the intent behind it.
The tactics and strategies laid out in this document are not just designed as a reaction to the deprecation of third-party cookies, they are also about creating the experiences that consumers have come to expect and are willing to trade their data for. A key aspect of these experiences is personalisation.
Personalisation can be a delicate tight-rope to walk; too broad and you’ll either give the consumer someone else’s message, something so generic it means nothing to anybody or you’ll display such a level of insight as to come off as creepy.
How do you navigate this?
Well, you’re a smart human being, consider the relationship you have with this person. Marketing relationships are no different to relationships in your personal life. For example: knowing your partner’s favourite underwear – not only acceptable but recommended. Knowing the favourite underwear of someone you’ve just been introduced to – definitely very fucking creepy.
Now that we’ve introduced some guidelines as to how personalised you should go, let’s dig into it a bit more.
Your personalisation efforts will all feed directly off the first and zero-party data you have gathered in the virtuous circle of CMS – GA – CRM. It will also be based on the segmentation you have done within your CRM, which is based off the personas you have created. Personalisation goes from the small and expected; your name on an email you receive, to having predictive analytics presenting you with a product option not because you’ve viewed it but because others within your profile have purchased it.
There exist a wide variety of tools to assist with personalisation but I’m keen to only present you with solutions that you will already have in your tech stack.
Your CRM will be able to handle a lot of the heavy lifting in terms of comms: email, sms, chatbot etc. Your CMS should be able to handle dynamic content; it will use identifiers such as cookie data or user ID ( all, as ever, with explicit permission). Ideally you want people logging into your site. This will not only allow you to progressively profile them, it will allow them to use their email as the unique identifier and present content to them accordingly.
You may require a plugin for your CMS to enable this and you may also find that your CRM isn’t up to scratch, in which case I can thoroughly recommend a look at Hubspot.
Email is one of the most common personalisation methods and still is an incredibly effective form of marketing communication, as mentioned, you want your email personalisation to go beyond simply including their name. You want to use the first-party and zero-party data you possess to have unique(ish) conversations with them.
You will have separated your contacts into lists within your CRM. This means if someone has completed a survey on their “why” you can combine it with their first-party transactional data in these lists. Which means alongside being able to know they like to visit Madeira frequently and booked 11 months in advance, you can personalise the email with further qualitative data from their survey and purchase validating info such as the weather report. Such as below.
It’s always nice when planning ahead pays off.
Not only have you saved money on your trip to Madeira on Tuesday 12th August, we can also see that the weather forecast is sunny with highs of 30 for all of your 10 day trip.
This means if you wanted to attend the Black Scabbard Fish Festival again you know the weather will be on your side.
As you will be on holiday for your birthday we wanted to give you a present – One free treatment at the Hotel Eden Mar – Enjoy
All the best,
Amy at Data Recipes Travel
This email is crammed full of personalisation (from 0 and 1st party sources) all of which will further strengthen your relationship with your customers. We know John’s name, that he’s an Early bird, the fact this saved him money, where he’s going, when, the weather, how long he’s there for, what he’s attended before when visiting, when his birthday is and where he’s staying.
It’s a crazy amount of information, but it should not come across as creepy as John will remember the survey he did, in exchange for something, where he told us the festivals he’s attended in Madeira before. Everything else contained he would expect his travel agent to know as he booked through us, but we will have been clear that we will use the information to provide him with more personalised experiences and benefits such as a birthday present at the hotel he’s staying at.
This is a classic example of personalisation and data exchange at its best and the key thing to the new approach to data. All explicit, so John knows exactly what to expect, but it’s also beneficial to John and to the travel company. He gets relevant and useful information, a business that understands his desires and tangible benefits for this. And the travel agency gets to build an open, strong relationship with John which will encourage him to tell us more about himself, strengthen our bond which will ultimately lead to him spending more with us more frequently and potentially becoming an advocate for us.
We can also take data directly from users’ web activity and use that to send them relevant and personalised emails. If users have been browsing certain products on your site you can send them related material to encourage consideration or purchase.
A final note on personalisation within emails, always have your email from an actual person in your company. Response rates are far better when you do this and remember; the idea is for you to view the relationship with your customers as a real relationship, like one you would have face-2-face with a person in your life, people have the best relationships with other people, not businesses.
Web personalisation is becoming ever more important to providing the rich customer experience the users have come to expect. The bar has been set high by companies such as Amazon and Google and people will expect the same from you. The form this personalisation takes will differ based on your company, industry and whether you are B2C or B2B, it can go from granular and detailed product recommendations to page layouts favoured by different profiles you’ve created within your CRM. Ensuring a good integration between CRM and CMS will allow for a greater range of personalisation options though a lot of it will come down to the existing stack you’ve got. Integration is the name of the game these days so you will likely find plug-ins or other platforms you can connect to help your exploits here.
Web personalisation, like most modern marketing, is about testing, learning and optimising. This means understanding which personas or individuals are going to engage with which content, and how you are going to track this.
Effective goal and event tracking within Google Analytics is a must here, as is a firm focus on your objective. There’s such a wealth of personalised options available that it’s easy to get lost in the opportunities without focusing on what’s helping you realise your objectives. You can display dynamic content in headers, hero images, CTA’s, product recommendations, page layout, body text forms and more. But the key is to understand what’s driving you towards your overall objective.
Let’s say you have a dynamic hero image, that changes based on the category of holiday your visitor likes to buy. A fan of sun, sea and sand? Here’s a picture of the Seychelles. Like to Ski? Then here’s a view of Chamonix. You could put this in place and see that your bounce rate drops and your click throughs increase – amazing right! Well only if those people are converting in greater numbers, more frequently, or for a higher value than before (assuming driving revenue is central to your objectives).
Now in reality, odds are, more personalised experiences will result in driving greater financial performance, but I’ve used the example above to try and demonstrate that your personalisation efforts (like everything you should do) are orientated towards delivering your commercial objectives.
Whilst we’re talking about not getting carried away with opportunities available, make sure to not let your dynamic content damage your SEO. If you’ve got some heavy lifting copy then carefully consider whether you want to sacrifice this for dynamic content.
Ads are obviously an area that will take a big hit from changes to third-party cookies. Re-marketing (for display not search) will take a hit, as will look-a-like audience as these rely on third party information. The fact is, whilst they will take a hit they will still be operational, maybe just not as efficiently. Tools like customer match will be unaffected as they utilise your first-party data.
It’s also worth remembering that these changes have been pushed back to 2023, so (at the time of writing) you have a year left to carry on using existing methods whilst you get your first-party strategy up to speed.
Once the change does occur, you will still be able to re-market using search ads and, word on the digital street is, use look-a-like audiences – they will just be broader and anonymised, using a cohort based approach.
As you will lose some of the personalisation available in ads, the key is going to be when and where you can use your explicitly gathered data for personalised ads.
Customer match is an area that will still be available for a fantastic level of personalisation and that is no bad thing. It’s easier to farm than it is to hunt – (and creating great experiences for your existing customers will boost their incentive as advocates) Upsells and cross-sells being the aim of the game. You can use your CRM and/or Google analytics to automatically update audiences within the Google Ads platform. You can then target your existing customers. It takes less effort, and importantly spend, to convert your existing customers than it does to convert new ones.
It’s important to not just whack all of your existing customer info in as one homogenous mass. Segmentation, again, is key. Want to sell a certain kind of product? Don’t just look for those who have bought it before, look for those have spent the most or spent the most frequently, target value within your segments.
The deprecation of third party data means that intelligent use of your own data is critical so use everything at your disposal: transaction data, interests (gained through 0 party data surveys). Using these you can make sure the future of cookies is one of your own making.
With all personalisation remember to use the data at your disposal (and explicit qualitative feedback) to understand how far to take your efforts. Yes personalisation will provide greater results but if you take it too far, you may deter customers. If you keep your data collection explicit and in a clear data exchange you should prevent this, but people may get unnerved if they feel you know them better than they know themselves, or are predicting life events (see Target knowing a girl was pregnant) then you may need to rein it in!
Stay tuned for the next instalment of Data Recipes – Future of Cookies
We’ve got so much awesome stuff to share with you but we’re going to drip feed it so it’s available in manageable bites rather than have you try and eat the whole cake at once. We’re just going to keep updating this blog so you can just keep returning here – a constant source of information and insight into the future of cookies and the different recipes you can cook up with first and zero-party data.