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A key theme at the recent Econsultancy Digital Cream roundtable on Personalisation was paralysis: being unsure how to prove the business case to justify investment and start the personalisation journey.

This uncertainty is leading to inertia as digital teams invest in what they know works, such as paid search, rather than take the leap of faith and pursue what they believe will work but don’t have a robust model to validate.

However, there are some simple steps that people can take to test the impact of personalisation before worrying about sophisticated options like using predictive modelling to drive on-site merchandising and geo-personalisation of online advertising.

This blog is a walk-through of what I think is a realistic roadmap for personalisation, starting with the absolute basics (hey basics often work really well so don’t think you’ve got to go all weird science straight away!) and gradually progressing to the sexy wizardry of advanced targeting.

I’m breaking this down to five steps (us consultants like to use numbers to make it look structured and well thought out):

  1. Early dawn.
  2. Branching out.
  3. Awakening.
  4. Enlightenment.
  5. Future sailor.

Feel free to scoff at my suggestions and pull apart my approach. If you have any suggestions/alternative approaches, please can you explain these by adding a comment to benefit other people reading the blog.

1. Early dawn: laying down the roots of personalisation

The key barrier to adopting personalisation techniques is an inability to justify the investment because there is no existing data model to prove the impact.

So you should start doing things that don’t involve buying in third party software or reengineering the website. Start simple and low cost and learn what works and prove to other people in the business it can have a positive impact.

For example, you can customise your brand value proposition and USP bar to show different content to new and returning visitors.

Free People, a US fashion retailer, does this by tailoring its delivery message for non-US audiences:

Free People USP personalisation 

Why?

Visit intent is likely to vary between these two segments. For example, new visitors are less likely to trust your brand and understand the key benefits to shopping with you.

Perhaps a 365 day returns message is more important to them than a return visitor who already knows this, or a statement about brand heritage to reinforce credibility.

You can use your analytics data to discover which areas of the homepage/site each segment turns to most e.g. which navigation elements do UK visitors click on most? You can use persistent surveys like Qualaroo & Kampyle to overlay qualitative data to help better understand intent and user journey barriers.

Translate this data into hypotheses about which messages each segment is most likely to be influenced by. Then make sure you have tracking in place to measure interaction with these messages e.g. clickable text that can be tracked as an event, or viewed on a clickmap.

Personalising real estate on the home page is often the quick win at an early stage as it can be done relatively simply via the CMS. The Wine Society uses a key content zone under the top navigation to show personalised information to members when they log-in.

It’s a subtle change but demonstrates how you can take small steps.

The Wine Society personalised homepage

The good news is that all of this can be tracked and measured easily. You can view page level data within analytics tools if you are creating new webpages, or you can add event tracking to specific content/on-page actions.

You can then segment reports to show data for new vs. returning visitors.

2. Branching out into marketing channels

There is a surprising (and quite frankly disappointing) amount of mass marketing still going on in digital channels, especially via email. The next logical step is to segment the customer set to do some basic personalisation of content & messaging.

For email, personalisation can start at the sign-up stage. Schuh, for example, uses basic segmentation to split visitors into buckets for Men and Women.

From the start, you’ll get email content that is more relevant to you than a generic broadcast trying to cater for both genders. Yes it’s basic but it’s another quick win.

Schuh email segmentation

You can then use your CRM programme to gradually add more customer level data (e.g. product interests, average spend, content interests etc.) to help you refine segments and drill down into a greater level of personalisation. 

Selfridges sends new email subscribers an invitation to personalise the emails they receive via a preference capture landing page. It’s simple and effective.

Selfridges email data capture

And what about social media? Imagine what would happen if you captured Twitter IDs in your database and then ran personalisation campaigns to a select few high value customers.

You could tailor an offer based on the products and content they visit and use Twitter to speak to them personally, not just rely on the next email campaign.

I’ve not seen this in B2C but I’ve personally received targeted tweets from B2B marketers/business owners I follow relating to past interactions e.g. contacting me about a new white paper based on the papers I previously downloaded/enquired about

3. Awakening: early shoots of automating personalisation

The next stage is to bring automation to the party, which requires development either through bespoke solutions or integrating third party software. In my experience, the cost of building your own algorithm to the level of sophistication of specialist software providers often makes the bespoke route unviable.

A good example is using learning-based algorithms to power on-site search so that search results are personalised based on:

  1. A visitor’s previous behaviour and the pages/products visited/bought/shared etc.
  2. The general behaviour of visitors searching on a particular search term – which products were clicked most, converted best etc.

The personalisation of site search goes beyond merchandising (although personalisation and merchandising are closely related), which primarily uses business rules to determine what to show people e.g. we want to prioritise all items that have high stock levels in all variants in search results pages.

The personalised version learns from visitor behaviour, so the results shown are related to their browsing activity and/or the general browsing behaviour of all visitors who searched on that particular search term.

The algorithm is set to learn continuously, so what is shown one week is likely to change the next. This is ideal for factoring in seasonal variations in visitor behaviour e.g. products viewed & bought at Christmas are likely to differ to those during the rest of the year due to the influence of gift purchasing.

There are tools out there that provide this level of personalisation. A good example is SLi Systems, which provides Learning Search and Learning Navigation. Boden is one of its Learning Search customers and you can read a case study of the results.

4. Enlightenment: real-time marketing personalisation

Real-time personalisation helps to customise ad content based on the user, for example using geo-targeting to promote products/services relevant to the user’s location.

Using a core template, the data management platform dynamically creates ads by pulling in the relevant content versions based on the user profile. It’s essentially a large MVT experiment to learn which ad structure and content works best.

This isn’t a distant dream. The technology and data driven companies exist to implement this right now.

For example, Infectious Media has worked with retail brands to create personalised advertising campaigns. It’s worth taking a look at this interesting video on YouTube where Peter Burns, Waitrose Online Marketing Manager, discusses its real-time advertising.

Here’s the low down from Attila Jakab, Client Services Director at Infectious Media:

Advertising can be personalised on many layers, who is targeted, where, at what time, and with what message. For Waitrose we used real-time advertising to target only non-customers who lived within the coverage of retailer’s distribution centres, biasing toward centres with spare capacity. 

We delivered advertising at times when consumers were receptive and on sites which were more likely to stimulate engagement. The creative was designed dynamically, pulling in pictures, offers and formats in real-time, based on individual consumer preference.

We also ran advertising for existing Waitrose customers, using data to provide offers that were relevant to individuals as they browsed the web. The adverts were specific to customer experience, for example, echoing offers they had seen in an email; offering money back from a second, third or fourth shop; or encouraging additional purchases on an existing order before a delivery cut off. 

Most retailers think you can only increase average order value on site, but marketing off site can have the same effect. If the results are compared to the previous year, average order value and shopper frequency increased dramatically and order amends nearly doubled.

5. Future sailor: seamless personalisation across web & marketing channels

To reach this point, you will need to integrate data sources to help create the single customer view. Consider a B2B company that provides IT software solutions and runs events to promote thought leadership.

If the data sources aren’t aligned, the marketing team won’t know that customer A, who has bought solution B, has also attended event C that was about solution D. They are then likely to miss promoting solution D to the customer in their campaigns because they’re unaware of the interest.

With a central customer view, you can tie-up all data points to create a more detailed view of the customer. For example, a department store like House of Fraser could know that customer X mainly buys from brand Y & Z online but in her local store, she actually buys more from brand A and spends more on average.

Through email marketing you can then use dynamic content to personalise at the customer level with relevant products and even segment the database to split out single channel customers from multichannel and then tailor the template to suit each e.g. multi-channel customer template has a content zone to promote the local store activities and promotions.

This data can be made available to everyone in the business who uses customer data to deliver service. Customer service agents (CSA) can have information surfaced to them when a customer calls in, as soon as they enter their account details.

For example, the customer recently attended a VIP event at the London flagship store for the launch of a new brand and the CSA is able to ask them about their experience and inform them of a new promotion on that brand.

All the data can be surfaced to the CSA at the point of call and use business rules to control what is shown and when e.g. if customer has an active complaint, don’t promote marketing messages.

Where are you on the personalisation evolution scale?

I’d be interested to hear from other people and learn how you or your clients have embraced personalisation and what you have learned along the way.

My personal experience is that many get the basics right but struggle to move on to the next stage, especially tying up the on and off site experience.

More often than not, this is down to data gaps, sometimes created by internal silos, but usually the result of not sitting down and planning data tracking requirements upfront.

OK, over to you now….

James Gurd

Published 21 October, 2013 by James Gurd

James Gurd is Owner of Digital Juggler, an ecommerce and digital marketing consultancy, and a contributor to Econsultancy.He can be found on on Twitter,  LinkedIn and Google+.

49 more posts from this author

Comments (21)

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Michaela Clement-Hayes, Communications Executive at FusePump Ltd

Good points, well-illustrated James. It still amazes me that some companies still fail to personalise their marketing.

I still receive completely irrelevant offers and information via email and Twitter and just yesterday was sent an e-voucher for dog food (when I only ever buy cat food).

I still think that more could be done with Twitter - targeting me based on users I follow, those I interact with regularly and the keywords I use in my tweets.

It will be interesting to see how companies use personalisation, social media and seasonal timing for campaigns in the weeks before Christmas.

almost 3 years ago

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Kate Nightingale

Great approach James. I like the fact that you're accentuating the in-depth knowledge of the customer and differentiating between new and old customer.

I have created this model of Consumer-Brand Love Relationship which likens consumer-brand relationship development to love relationship development between 2 individuals. It highlights the importance of the differences in marketing based on the stage of the relationship and individual differences between customers such as age, personality and the type of attachement ot the brand.

So I'm really happy to your 5 step model recognises these aspects of the relationship as really important as not many companies are doing it yet. And in the era of extremely well educated consumers with high confidence of choosing only the brands that really take care of them and take efforts to get to know them, those that take action to improve that relationship and build long-term loyalty will survive. It's like marriage, if you won't work on it, it won't last long.

However, even though we see bigger interest in data and personalisation, there is still little understanding of the people behind the clicks. It's like the e-commerce professionals forgot that it's actually people and their twisted psychology that's behind every behaviour online. Once you remember that and understand what some online behaviours mean on a human level, you can do so much more with your marketing.

almost 3 years ago

James .

James ., Director, Digital Strategy & Optimisation at Personal

Hi James,

I like the fact that your article builds up in in level of complexity both at level of personalisation you can offer at each level and in turn, the potential level of investment that might be required to achieve it.

I believe this sort of structure and advice can be exceptionally useful to those who operate within small and medium sized businesses that want to adopt a personalisation development policy as they know the potential rewards for both the user and the business but are not quite sure where to start.

I do think that as personalisation evolves there is a point where, as Kate mentions, we need to remember that there are actually people behind the visitor statistics. Therefore it is important to work to combine the online and behavioural data and compare it periodically to customer persona data and qualitative research so the the feeling (UX) behind the action.

By ensuring we continue to combine the quantitative, qualitative and human elements, it allows us to enhance the online offering, make the user/customer feel satisfaction and increase online revenue.

almost 3 years ago

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Chris Michael

Nice and simple approach. Thanks.

almost 3 years ago

Mike Austin

Mike Austin, CEO at Triggered Messaging

Great article, and an area we're really interested in, and - full disclosure - provide services in.

Setting up personalization can be a steep mountain to climb for most companies. You're right to address the point that collecting the data together makes this near impossible for the average marketing manager. We make this easy.

The other point that should be considered is how you can use the crowd-sourced data about what your shoppers are doing en masse. What's the hot products in your catalog? Can you take advantage of current trending products/sectors automatically? To do this effectively, you need content to be created automatically based not just on the individual behaviour, but the crowd-sourced data about what all your shoppers are doing.

More on individual and crowd-sourced personalization:
http://www.triggeredmessaging.com/real-time-marketing/engage

almost 3 years ago

Pete Williams

Pete Williams, Managing Director at Gibe Digital

looking forward to digesting this properly and seeing where we can employ these ideas. Loving the nod to the Mighty Boosh!

almost 3 years ago

James Gurd

James Gurd, Owner at Digital JugglerSmall Business Multi-user

Morning all,

Thanks for taking the time to share your thoughts/experience and good to see that personalisation is an interesting topic.

@Michaela - yes I think social channels have great potential, from the basics of replying to people who are commenting to extracting the data, overlaying other data sets and creating targeted campaigns.

@Kate - your Consumer-Brand Love Relationship model sounds interesting, are you able to share it with us?

@James - yes understanding the customers is hugely important and for me the biggest challenge. How can you infer intent based on specific actions? Correlation isn't always causation. For example, i buy product X as a gift for a friend and spend weeks researching it. Do you then promote products related to X? The crunch is developing learning algorithms that can crunch all data points to come up with a relevancy rating to help strip out isolated events.

@Chris - glad you liked it.

@Mike - who do you think does this best? Who have you worked with that 'gets' personalisation and uses data in a clever way?

@Pete - brilliant, someone else picked up on the Boosh nod! That has made my day!

Thanks
james

almost 3 years ago

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Ernests Stals, CEO, co-founder at Reach.ly

James you have broke it down really nicely.
Actually in first two steps most e-commerce sites experience biggest jump in conversions because they are approaching so called "low hanging fruits" of personalization which affects nearly every visitor/customer.
At Reach.ly we are after step three - understanding customer behavior. Do they have intention to purchase, are they just Surfers with no intention or Samurais who rush in and grab product in 5 clicks.
I think future of personalization is going to be in direction of semi-supervision - algorithms will help to find interesting insights but it is up to human to figure out action they want to take on particular group of customers. For example it is possible to find 50 Surfers and predict three products they might be interested in. But it is up to site owner on which channel and with what message to communicate. Is it personalized e-mail after three days of visit, or is it onsite block, maybe it is discount coupon overlay. Or maybe it is retargeting on some Real time bidding system.

Ernest @ reach.ly

almost 3 years ago

James Gurd

James Gurd, Owner at Digital JugglerSmall Business Multi-user

Hi Ernests,

How are you? Hope things are going well at Reach.ly.

You're right that understanding customer behaviour is really important and that a blend of computer learning + human skills is required.

I think a real challenge is in understanding customer segments and personas - it's really hard to infer intent just from the data, you need to at least have some concept of who the customers are, what are their general characteristics, personalities, likes, dislikes, desires etc. So there's a broad skill set in use, from web analytics to segmentation and psychographic analysis.

When you have the answers, let me know!

cheers
james

almost 3 years ago

Mike Austin

Mike Austin, CEO at Triggered Messaging

@James
One client I can talk about is Alexandalexa.com. We drive their cart and browse abandonment emails, which are fully personalized with relevant products. The browse abandonment emails gave them a big lift in conversions - these contain the most recently viewed products, plus a set of products that look relevant based on prior behaviour.

We have other clients who use browse and purchase-based personalization within their regular email campaigns, but sadly I can't talk about those at the moment. They get significantly improved conversions. Importantly, they also have to do a lot less work to setup the campaigns with relevant content, because it's generated for them.

Hopefully will have a case study to share soon.

almost 3 years ago

James .

James ., Director, Digital Strategy & Optimisation at Personal

@Mike

I was aware that you offer cart abandonment offering and understand how you can email individuals that abandon as normally people will enter an email address to enter the checkout process.

I am just wondering how can you identify and target browsers who have visited a site, viewed a few items and then left? Do you still need them to enter an email address at some part of the process?

Thanks

almost 3 years ago

Mike Austin

Mike Austin, CEO at Triggered Messaging

@JamesA
We can capture email addresses in various ways, including:
* When they login
* When the subscribe to a newsletter
* When we've seen that person before.

So browse abandonment works best where shoppers have a pre-existing relationship with the site. It doesn't help with new people who come in via search or affiliate - for those parts of the puzzle, we offer on-site personalization. If they leave the site without identifying themselves and giving permission for emails, the only option is to go to one of the retargeting ad networks.

almost 3 years ago

James .

James ., Director, Digital Strategy & Optimisation at Personal

@ Mike

Thanks very much for clarification.

I will make sure I check out the website and read up on the browse abandonment in further detail.

Many thanks

James

almost 3 years ago

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Tom

Nice and simple. Great stuff.

almost 3 years ago

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Iulia Gheorghita

James, great article and a nice break-down - very realistic indeed. Interesting to see that it all comes down to understanding the customer/ prospect and targeting based on location and behaviour. One thing we know for sure, there is more to a customer than location. And tracking their behaviour on the website is doesn't seem to be enough information to convert into business.

Organisations need a fast-track and as more data on their customers in order to build deeper understanding. This is an area we are keen on; we built the technology to provide businesses with customer insights to append to existing records.

We also cover the events point you made above: http://www.datafreshup.com/event-graph/

over 2 years ago

James Gurd

James Gurd, Owner at Digital JugglerSmall Business Multi-user

Thanks for dropping by with a comment @Lulia.

I think the key challenge with personalisation is understanding customer intent and need. All the data in the world can't tell you why someone is doing something, you need the ability to interpret the data and make hypotheses about customer intent. It's an imperfect science as we're all individuals but it's possible to do predictive modelling to personalise content.

Thanks for the link to the Event Graph, certainly an interesting way to profile people for event targeting.

thanks
james

over 2 years ago

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Iulia Gheorghita

Thanks for your reply @James.

You're absolutely right. Analysing existing customers or website visitors' behaviour is definitely key in understanding intent and is a good place to start with personalisation.

When it comes to re-connecting with an old client who hasn't been in contact with your business for months, I think investing in personalisation (and going beyond the company domain) definitely pays off as it allows you to go where your customers/prospects are, online.

Thanks again for the article. An interesting topic and an area that has so much to offer.

Iulia

over 2 years ago

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Melissa

Nice tips on personalization, James! It's time that marketers realize how important real-time personalization is. One of our retail customers began greeting international shoppers on its website with a welcome message that conveys trust and benefits: "Secure and cost-effective shipping to more than 200 countries, full duties and taxes billed at checkout, direct tracking to final destination, delivery timeframe, etc." Their carting rate increased 162% since launch and they've got plans to add more personalization features.

Here's another good eConsultancy article on how to achieve personalization: http://econsultancy.com/us/blog/63295-simplifying-personalization-three-ways-every-online-business-can-achieve-it-today.

over 2 years ago

Ashley Friedlein

Ashley Friedlein, Founder, Econsultancy & President, Centaur Marketing at Econsultancy, Centaur MarketingStaff

Great post as ever James. Good see a practical 'how to start / progress' guide to addressing personalisation.

Here's a quick alternative model I've just dreamt up. 4 stages each with basic and advanced levels...

Stage 1 = Customisation
This is not based on PII (personally identifiable information) but contextual data like location, time of day, referring search string etc.
Basic level = customising based on location (e.g. price, content)
Advanced level = customising based on behavioural patterns over time e.g. showing different content to repeat visitors vs first time visitors

Stage 2 = Recognition
This is based on PII when customer is known. Unlike above it is also clear to the customer that they are being recognised as a unique person
Basic = using name in communications (on site, email etc.)
Advanced = combining name with other data to personalise comms e.g. birthday, transactional history

Stage 3 = Segmentation
This includes (re)targeting. Personalised experiences based on which segment you belong to. Segmentation could be based on RFM type models.
Basic = segments of more than one
Advanced = "segment of one"

Stage 4 = "Omnipersonalisation"
A new buzzword! Now with 'omni'! This is where the personalisation is present wherever you go, online and offline. You deliver experiences based on context, device, time of day and all sorts of other variables. Data + Content + Personalisation Engine + Rendering/presentation engine.
Basic = omnipersonalisation based on past behaviour/data
Advanced = predictive omnipersonalisation...!

Arguably something like Google Now is closest to predictive omnipersonalisation...?

over 2 years ago

James Gurd

James Gurd, Owner at Digital JugglerSmall Business Multi-user

Afternoon all,

@Melissa - i think it should be made illegal to not at least personalise UPS bars to non-domestic visitors. So, so simple to do.

@Ashley - I thought buzzwords were on Graham's editorial execution list?!

I like the model, especially as it gives basic/advanced at each stage which is helpful. Thanks for your take on this.

There are some great examples of predictive personalisation.
The new Fraggl app is one - curated Twitter content based on your profile and predicted interests. Neil Perkin is one of the creative brains behind it.

thanks
james

over 2 years ago

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lllll ashton, solutions architect at virgin holidays

Just read this so perhaps a little behind the future sailor curve. Massive Boosh fan.

Good article, lots of food for thought. Cheers

over 1 year ago

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