cookieOK, so cookies are actually only mentioned one time in GDPR, but that one time packs a bit of a punch.

Natural persons may be associated with online identifiers… such as internet protocol addresses, cookie identifiers or other identifiers… This may leave traces which, in particular when combined with unique identifiers and other information received by the servers, may be used to create profiles of the natural persons and identify them.

Which translated basically means (taken with other parts of the regulation) if you can identify an individual via their device (directly or indirectly) that makes it personal data.

Now not all cookies will be able to identify users but a whole load of them are. And that includes analytics cookies.

The existing “cookie law” was pretty clear about gaining consent and we all added those cookie bars on to our websites that basically implicitly gained your permission. Well those aren’t any good any more. For any cookies that aren’t strictly necessary to run your site you’re going to have to get explicit consent under GDPR.

That means you need some kind of affirmative action. Like a tick box.

And that consent must be as easy to take away as it was given.

Oh, and it’s about consent. So if you’re not giving a choice then there’s no consent to be given or not. Which basically means you can’t tell your visitors they have to accept or the can’t browse…

Insight at the heart – changing culture

img_0032I have a mantra. It goes like this: you cannot call yourself customer centric unless you are first data centric.

In other words, your data (and the insight you service from it) will tell you so much about your customers that if you’re not using it to the absolute maximum then you can’t be providing the best to your customers that you can.

But shifting the culture in an organisation is tough. You can stand up on your soapbox and suddenly proclaim that your business will make decisions based on data, but those are just words. How do you get everyone to follow?

For me the greatest successes I’ve had in getting big organisations to start being more data and insight focused is to start small. Put away that soapbox and instead start building a movement behind you. Get a couple of senior stakeholders bought into what you are trying to achieve. And then get a couple of your peers bought in too. And between you start to create a plan of action and sketch out your processes.

And then get on with it. Accept you won’t get everything right immediately. But because your movement is small it doesn’t matter. You haven’t gone out there and promised the Earth. You can learn and try again.

And once you have a couple of really good wins behind you, start talking about it. Again, don’t go out there with your big bang, but just build your movement out a little further and embrace a few more followers. Keep your senior stakeholders in the loop and excited about what you are doing, and continue to test and learn as your new followers come on board.

When you feel like you have a bit of momentum behind you and crucially you have strong processes and governance in place (good quality data, people, escalations, etc) then go ahead and talk a little more widely and a little more loudly. More people will jump on board. You’ll have a few more challenges and you will evolve but that’s only to the benefit of the movement.

This won’t all happen overnight. You will need to be in it for the long run. But you are more likely to have sustained success and growth this way than shouting at people to follow you (or in some places I’ve been in, to just fucking do it…).

Google and automated insights

Robot armGoogle continues to add some interesting features to Google Analytics, and one of the latest is the ability to get automated insights.

It uses Google’s machine learning to comb through the data you have and comes up with a stream of what it calls automated insights.

For some reason they have decided to make this feature available in the Android and iOS Google Analytics app, but not the desktop interface (presumably they want more people to take the app right now…).

In the Google Analytics blog announcement which you can read here it specifically calls out “marketers, business owners, and product designers” but doesn’t mention analysts at all. 

I’m a bit fan of automation when and wherever it makes sense. But I’m still not yet convinced that machine learning is clever enough to properly interpret everything that’s going on and the danger here is that people without full knowledge make bad decisions because Google Analytics told them too.

A little bit of the cynic in me says a lot of the “insight” that Google Analytics users will be seeing will be telling people they need to be advertising more with Google…


helpThere is no right answer to creating a good online self-service environment, but there are some strong best practice pointers that will help guide the way. Not everything will be suitable for every business.

Here are some pointers though!

  • Ensure you have joined up web analytics and reporting, including contact centre, voice of the customer and web data.
  • Use simple classifications to help people filter quickly and easily.
  • Don’t have long lists of FAQs. Have a clear list of top questions, and then have a clear path for other users to filter to the right answer.
  • Make sure your search engine is capable of using natural language queries, and that it provides a small handful of relevant results. Implement a “did you mean” feature for clear filtering, and include either automatically corrected spellings or corrections.
  • Not all content has to be provided by you. Other sites might be better able to answer the question.
  • Have a user forum/community. Your engaged base will help out other customers in need of help. It’s also good for SEO, helps with appropriate escalation and is good for the brand. Ensure the community is fully integrated into your online help solution, including search.
  • Consider using video for your high traffic solutions. But also consider using your engaged base to help make those videos, and reward them for doing it.
  • Add a full customer satisfaction survey, and if possible include session replay.
  • Identify areas where contact is required, and ensure escalation points are clearly signposted. Finding an answer should be easy, even if that means the customer has to make a phone call rather than spend time searching the website. Consider web chat for help.
  • Ensure content is accessible on mobile.
  • Allow people to rate every answer on the website. This helps compliment web analytics with a partial voice of the customer. It also helps to weed out potentially poor answers for continual optimisation.

Ensure you use consistent language across your digital touchpoints, from purchase to account management to online help, store and the contact centre. Create a language bible that is shared across the business. For example, a talk plan should be referred to consistently across the brand.

Don’t work in silos. Some lessons from the US:

“A lack of coherence can damage brand image, and because of the confusion caused by the variance in navigation systems, could lead to frustration on the part of the customer and to increased calls to the telephone help desks.…support has a different look and feel and uses a different menu system. This can also slow the customer down when looking for help. Customer confusion poses a significant challenge, as visitors’ patience levels are low”[i].

Furthermore “…best practices demand that businesses be equipped to manage the customer experience via the preferred channel of the customer – whether it’s online via self-service, online via assisted service, or offline through a phone or in person. For some businesses, this process can be hindered by silos of informational hierarchies – with marketing owning the web site, contact centre owning many of the customer interactions and with neither communicating effectively with the other.”[ii]

[i] Verizon report, Customer Respect Group, 2010

[ii] IntelliResponse, Web Self-Service: The Cornerstone of Multi-Channel Customer  Experience Management

Social shopping?

facebook logo thumbs upShopping is historically a social experience, of that there can be little argument. It was online shopping that made it a more solitary experience. It seems only logical that people would like to bring back that social element while retaining the convenience of shopping online.

It is not yet easy to pick through the various statistics and review what businesses have done so far to come up with a single answer. Indeed, it’s still probably too early for there to be any kind of established route into making online shopping more social. There are also some trust and privacy issues that some of the social networks must iron out.

But if there’s no clear route, there is a clear business rationale, and that is to sell more. Inherent in that goal is the building of your brand, extending reach and the development of a long-term relationship with your customers to lead to deeper loyalty.

So how do you do it?

You have the pioneers like JC Penney and GameStop who have jumped straight in with full transactional apps on Facebook. Then you have people like BestBuy US who feature their products on Facebook, allow you to share and comment but ultimately lead you back to their site to close the deal. And then there’s the Levi’s approach, which keeps everything on their own site, but integrates with Facebook to allow people to share and comment on their own news feed.

Many of the retailers currently leveraging Facebook have something in common; JC Penney, GameStop, ASOS – these brands sell products that in reality require very little consideration and are largely self-gratifying (clothes, video games, etc). It is highly possible that Facebook shopping in particular is more about impulse buying of lower cost, lower consideration products.

Keep control.

If nobody truly knows the right route to follow, then there are at least some common principles:

  1. Your brand has to be on Facebook, YouTube and Twitter
  2. Don’t use social media to bombard your fans with constant sales messages. Build your brand, build trust and develop your relationship (but don’t bribe with competitions every week or discount coupons).
  3. Update regularly and consistently, but not for the sake of it
  4. Experiment, be brave and evolve, but make sure everything is measurable.
  5. Watch what others do and don’t be afraid to copy.
  6. Leverage social media in your brand campaigns and be confident about it, but continue to use retail spend in the channels that provide the best quantifiable ROI
  7. Facebook shopping will probably be for lower value, low consideration impulse purchases. Accept this and leverage it if you can.

The world of shopping on social media sites is going to evolve and change quickly. If you are going to jump in you need to do it properly and ensure that the benefit to your business is both measurable and quantifiable.

The future of digital retail

Abstract image

Retail is changing. Multi-channel is now firmly established as a consumer necessity, from click and reserve, any channel returns and super-fast delivery. It is also not just younger, agile businesses who are embracing a new approach. Tesco, John Lewis and Argos are hardly new entrants to the retail market, but they are some of the leaders. This isn’t a UK phenomenon either. In the US it is also established businesses such as Macy’s and H&M who are right at the forefront of innovation and experimentation.

There is no magic formula to create a successful digital retailer, but there are some clear emerging principles:

  1. Align with the aspiration of the customer and their changing habits
  2. Be committed to investing in and implementing change
  3. Have channels that are interdependent, not in silos
  4. Have a consistent brand view across all channels
  5. Have a single view of the customer
  6. Have real time analysis and insight
  7. Deliver a personalised customer experience
  8. Be clear on sales attribution
  9. Be clear on the role of the high street
  10. Test, learn, optimise. And do it over and over again.

Consumers are comfortable mixing shops, digital touch points, call centres and catalogues.

By having a digital presence across all touch points businesses are offering a clear benefit to consumers who are then able to make the choice as to how they want to interact with the brand.

There is inevitably organisational change that is a prerequisite to becoming a successful multi-channel business, but the perfect solution will evolve over time. The important step is to start.

Customers just want to shop with the brand, regardless how a retailer might have organised himself internally.

Businesses would do well to keep this simple philosophy in mind – test, learn, optimise, iterate.

At the heart of digital retailing is a mindset: a willingness and ability to understand and respond to emerging trends and changing behaviours. It is imperative that businesses evolve their model as consumers’ needs and behaviours evolve. And a genuine commitment to this approach is required, through failure as well as success.

So while much of digital retailing is in its infancy still – NFC, location based apps, social buying, interactive advertising – it is undeniably growing quickly. At the very least businesses today need to be multi-channel and starting to experiment with what it is to be a digital business.

Image © Chrisharvey

Why customer experience trumps everything

nWzdzmeI’m a very strong believer that for a business to truly succeed and make lots of money, they really have to focus on having a fantastic customer experience.

Yeah, you can make money by having a decent enough customer experience (Amazon?), but if you really want to hit the g-spot it has to be fantastic. This type of experience leads to higher revenue because you get either / or repeat business or referred business entirely for free.

But how do you create a fantastic digital experience? Well, if I could bottle that and sell it I would be relaxing on my own private island somewhere hot and sunny. Because the truth is there is no formula for creating a fantastic digital experience (and indeed, it should stretch beyond digital for clicks and mortar retailers). It will differ from business to business, and not only that, it will continually change and develop as the people who use those experience develop and change.

But what you can do it stay in tune with those changes? Using your web analytics tools, layering on your surveys and user research and testing and things like session replay. Basically it’s staying on top of your game. I’m probably preaching to the converted, but after working for more than 10 years in digital analytics I’ve seen the eye taken off the ball far too many times.

This little piggy…

Ho21rvpSow do you slice up which of your marketing channels get what slice of the attribution pie?

Hopefully we have moved beyond simply assigning everything to last click. And hopefully we’re well beyond first click.

So which direction do you take?
Well, let’s take what Google Analytics has to offer. If you haven’t explored, you can find it in “Conversions” > “Attribution” > “Model Comparison Tool”.
I’ve already talked about last click. It’s just plain wrong.
And first click. It’s just wrong too.
Linear attribution is less wrong that first and last, but frankly there’s gold, silver and bronze and someone deserves the gold. It’s a little mean not to give last click the gold, right?
The time decay model says the more recent the click, the higher up the leaderboard (the gold medal!). You just need a half-life. 7 days, 30 days? 90? And that depends on your product.
What about a position based model? 40% to the last, 40% to the first and the rest distributed to all the other channels? Well, we’re getting there!

So what about a more motive based attribution model? Taking into account a little bit of research before purchase, this would be a position based model, giving a last click the gold medal (say 40%), and first click a runner’s up prize (say 10%) because without that first click you wouldn’t even have had the first date. And then giving the rest to the channels in between.
But then how do you distribute among the other channels? What about an engagement metric? How deep into your site did they get? How long did they spend. Maybe adding extra weighting to social if you were running a big social campaign, and correlating any timings of your offline campaigns with online activity.
The upshot is, you can have an attribution model like the one I suggest above, but the metrics that make up that model may well have to change with every campaign you run.

There are certainly logarithmic models that have been developed and continue to be developed (ask your agency!). But be wary that a one size fits all might not be suitable.

I hate “big data”

mf6CKEMBig data? That’s a term we hear mentioned a lot, but what does it really mean? As businesses we have loads of data? Well that’s true. In truth we’ve always had lots of data to play around with, it just came in different formats and from different sources (sales data, footfall, even web log files).

Yes, we now do have so much more. But it’s only as big and scary as you want it to be. “Big data” is a term that, in my view, is all too often  used to sell you more services to try and make sense of it all. I’m not saying these are wrong though, but…

…the danger is running before you can walk. It doesn’t matter if you have loads of data that you’re not even touching right now if you don’t understand the questions you are being asked, or the questions you should be answering without being asked.

Don’t add on expensive session replay if you still have a poorly implemented web analytics service that you’re not really using to full effect. It’s a guarantee that there will be both quick wins and deeper levels of optimisation that you can extract from your web analytics tool without trying too hard.

If you’re ready to add extra levels of digital analytics, whether session replay or surveys or testing capabilities, then you won’t be fearful of “big data” because you’re already scaling your capabilities.

Don’t let anyone tell you you need a full suite of analytics from day one to gain a deep understanding of user behaviour on your site or app. Eventually you will have a full suite, but build it up in layers.