Multichannel Marketing – 2 years later: Digital is at a crossroads now (part 1/3)

In the two years since publishing the Multichannel Metrics book, the face of marketing has changed drastically.

We are entering a critical crossroads in 2010.

By 2013, will we look back and find that this was the year when marketers from online and other marketing teams first realized how similar their goals have become and took steps towards integration across camps?

Or will we look back and find that the camps remained ignorant of each other and instead set in stone silo’d technologies making integration more difficult than ever? 

 

What do you mean, web and direct marketers’ goals are aligned now?

Marketers have had no choice.

Greatness has been thrust upon them!

Direct marketers

  1. Have seen marketing dollars beginning to shift from offline to online
  2. Finally see clearly that a large portion of interactions with their customers has moved online. For example, according to anecdotal feedback from several older European banks, 25% to 50% of their clients use online banking now. Some financial institutes acquire the majority, if not all, customers online.

Online marketers

  1. Have had to abandon their silo’d, website-centric thinking because their websites are now only one component of their total web presence. Other presences include social media, mobile sites, behaviorally targeted ads and personalized emails.
  2. They may continue to treat the offline as a step child for another couple years. Yet, they are already adopting multi-online-channel marketing practices for the purpose of integrating all these web presences.
  3. The latter has required them to move from their traditional focus on aggregate level metrics and dashboards to looking at data about individuals across website, mobile, social, and advertising. This experience with individual level data will also make it easier for them to integrate their customers’ offline interactions down the road.

As a result, both online and direct marketers are now pursuing multi-channel data integration at the level of individual prospects and customers. Both camps do this for the purposes of

  1. behavioral targeting,
  2. better understanding of marketing ROI.

 

The technology gap is closing

While all vendors talked the talk for 360 degree views, the reality was different. Web analytics data was far removed from a direct marketers’ access.

  • After all, the data are owned by the web team who couldn’t care less about individual level data at that time.
  • The data are also hosted remotely at SaaS based web analytics vendors that prioritized reporting and good looking charts over granular data. As a result, data feeds (while available) would come with no SLAs. A feed might or might not arrive at the agreed time of night. That made it too unreliable for driving interactive (let alone real time) marketing programs.

Meanwhile, web marketers could integrate analytics based targeting into email marketing only by bridging the gap between several vendors and paying for integration services.

These technology gaps are now increasingly closing.

  • Omniture is positioning its online marketing suite along with integrations with ESP partners through its Genesis program.
  • Unica is positioning both
    • Its eMessage and Interact products for email and web personalization integrated with Unica’s web analytics and campaign management products for enterprise clients
    • Its recently launched Interactive Marketing OnDemand product where SaaS based customers use web analytics, email, and web personalization within a single application and UI.

 

The crossroads

This alignment of methods, goals, and technology represents our arrival at a crossroads.

(note added on March 12th): Maybe the word alignment is too much said.  But methods, goals, and technology are now more parallel and similar than ever.

But will we leave these crossroads into an integrated future or will we set in stone two silo’d multichannel worlds between online and direct marketing teams?

That is the big question.

In part 2 we will look at direct marketers vs. digital. Then in part 3 we will review where multichannel web marketing stands in 2010.

Stop acting like a loner, ‘cause web marketing optimization is a team sport!

I have to say, I am growing increasingly annoyed with the silo’d nature of the discussion that seems to still be dominating our web analytics industry.

We have been so silo’d that, for example, even something as adjacent to web analytics as audience measurement and its vendors (i.e. the comScore, Hitwise, Compete of the world) seem to appear more like second class citizens in our discussions. Meanwhile, 90% of the chatter among web analytics vendors, consultants, and bloggers seems to focus only on core web analytics topics and vendors.

A symptom that should give us pause is that most of our guru authors and bloggers – who are such rock stars to us web analytics people – are utterly unknown outside our little niche. Forget offline marketers, not even other online marketers know them!

Surely that isn’t because “the others” are all stupid and don’t understand performance optimization.

Honestly, I don’t know exactly why we seem to be such a silo’d breed. It is probably just a function of specialization in the workplace. Web analysts handle web analytics tools, multivariate testing, voice of customer, and maybe participate in behavioral targeting. But

  • Who owns audience measurement / competitive intelligence? Probably a shared function with marketing/PR?
  • Who owns social media monitoring? More often the “social media manager” or PR rather than the web analyst?
  • Who owns search optimization tools? SEO and PPC teams, of course. (And they too can be separated from each other in larger organizations)
  • Who owns email marketing? The direct or customer marketing functions.
  • Who owns ad servers and behavioral targeting networks? The online marketing or media team
  • Who owns site performance? IT
  • Who owns the replay stuff? Web developers?

If there is any way out of this strange situation it is probably to be found in embracing the different aspects of web marketing in a more balanced fashion instead of losing ourselves in increasingly nuanced web analytics details that seem esoteric and boring to people outside our niche.

Might we find bigger gains in 2010 by looking more for a breadth-first approach vs. continuing our deep dive?

Take search marketing as an example

The diagram below shows the search marketing funnel starting from potential visitors, i.e. users of the search engines (or their content networks). The search marketer aims to acquire them on site and then lure them deeper into the funnel to engage, persuade, and convert.

semfunnel1

The diagram then lists the different categories of marketing tactics and technologies that are involved in moving prospects through the funnel. Let’s take a deeper look at each category.

1. Audience measurement and influence

This category includes more items than one might think at first glance, namely the following.

Tool Example of how it helps with search marketing
Keyword research tools Which keywords are being used in general?
Audience measurement or competitive intelligence tools Which keywords work for your competitors and what is your share of those keywords
Social media monitoring tools Which keywords are being used by your audience? If your search clicks are up/down is that because there is a spike of positive/negative buzz about you?
Advertising, online and offline With improved awareness and perception of your brand, your audience is more likely to click on your search listings

 

2. Search marketing

This category includes the most obvious items associated with search marketing optimization:

Tool Example of how it helps with search marketing
Search bid management tools or agencies Reduce manual efforts and increase returns from your paid search budget
SEO tools or agencies Help monitor your success vs. competition for ranking better on critical keywords

 

3. Landing page management, and 4. site management

These categories include similar items that I shall list together here. But it makes sense to keep them as two categories because the vendors/tools for landing page management are sometimes not the same ones as those used for managing content on the rest of the site.

Tool Example of how it helps with search marketing
(Landing) page design and deployment To make split testing of landing pages for reducing bounce rates feasible it needs to be easy to create and deploy alternative test candidates
Multivariate testing Multivariate testing can evaluate even more permutations of test elements on a single page.
Voice of customer The numbers don’t tell the whole story of why visitors searching for XYZ do or don’t buy. So you need to ask them.
Personalization or behavioral targeting Going beyond testing, dynamic content that is targeted to individuals based on their past and ral time behavior has the promise of increasing conversion rates further
Lead management For businesses where the sales cycle continues offline it helps for improving offline conversion rates to tap into the prospects web behavior. For example the salesforce automation system can be updated with past and ongoing web searches that the prospect does.

 

Not to even mention product recommendations, product reviews, etc.

Is that all?

No, there is much more that is critical. Search visitors will often not convert on their first visit. So re-marketing is essential.

semfunnel2

More importantly, maybe, the customer life cycle doesn’t end with the first purchase. That is in fact when the work of the customer marketer only begins and the life cycle continues with on-boarding, growing lifetime value, attrition risk detection, and win back. Some additional tactics and technologies that are involved on the online channels include the following:

5. Interactive Marketing

Tool Example of how it helps with search marketing
Email marketing The lead is nurtured with content that keeps their interest alive and brings them back to the site until they convert (again).
Re-marketing ad networks The lead is reached on other (publishers’) sites with ad banners that are relevant to their past searches
Interactive Marketing (or next-generation campaign management or event-triggered marketing) By building all interactions on each individuals’ past and current behavior on the web channel (and beyond), the marketer aims to keep their messages (both timing and content) aligned with the individuals’ interests.

 

Do we really need all of that … stuff … to optimize search marketing?

If your goal is merely to improve search marketing, e.g. PPC, you need nothing more than a Google AdWords account while paying attention to the built-in couple of metrics. But if you are after optimization, then the above are truly all part of the funnel or chain. Each of these pieces are truly needed and will pay for themselves.

And we are supposed to integrate that with web analytics?

As a supporting function and nerve center, web analytics has the potential to glue most of these elements together. When done right this could make your web analytics people some of the best known employees across all of these teams.

But you would be forgiven if you are thinking that integrating all of these functions with web analytics could be too big of an effort and cost. That is precisely why vendors such as Omniture and Unica are building out online marketing suites.

Today, not all of the above are available (and integrated) within one vendor’s suite. But that day will come because there is a real need by marketers.

Announcing: Free Optimization Wizard for Organic Search (SEO)

“The best things in life are free”, they say, and organic search traffic might seem free at first glance.

But in truth, as you will know, organic search isn’t free at all. It requires hard SEO work upfront before you can rank well for highly coveted keywords.

This wizard is for any marketer looking to get more business results (traffic + outcomes) from organic search (and who doesn’t?).

It walks the analyst through a series of steps for increasing results, e.g. by identifying the keywords to prioritize for SEO, doing the on-site and off-site SEO, and optimizing your web marketing for organic search visitors.

Web Analytics Question Support System for SEO

Click here to start the SEO wizard


Bird's eye view of this SEO wizard
Click here for a bird’s eye view, i.e. summary flow chart

This wizard is the third example of an expert system that I got a chance to work on now. The wizards aim to help web analysts (and in this case also search engine marketers) with their complex work. Earlier releases were the wizards for PPC optimization and troubleshooting a drop in website conversions.

Couple comments and observations:

  • As always I would like to point out that these wizards can neither replace the need for experienced SEMs nor web analysts. The goal of the wizards is just to make their work more systematic.
  • A good example of why this is true may be the following. Namely, for any specific website, an experienced SEO can probably point out the 20% of the steps in this wizard that will help achieve 80% of the results. In contrast, in the wizard all recommendations seem to be of equal priority / importance. That is a bit of a flaw with this SEO and also the PPC wizard, I have to concede.

As I am not an SEM myself (neither SEO nor PPC), this wizard will only become truly exciting with the help of user comments that can be added to any step of the wizard.

Look forward to hearing what people think and hope that this proves helpful.

This Thursday: Web Analytics for Driving Your Entire Business (not just your Website)

This Thursday, Angie Brown from Elsevier is presenting live in a webinar within the Web Analytics Association’s webcast series. She is going to share some very clever examples of her web analytics work at the publishing giant.

I had the chance to listen to Angie’s presentation live at Unica’s annual customer conference earlier this year in Paris. Her anecdotes about using web analytics to inform offline and other strategies showcase that the insights go much further than just to improve the website or advertising.

As the webcast is sponsored by Unica, I will get to follow Angie’s featured presentation with a few words on Unica’s view of next-generation use of analytics.

Register here to attend live on Thursday at noon US ET or to receive the recording link after the live event.

Social Media Metrics to Fit Your (Secret) Business Goals

Social media are challenging and humbling. The discussion of how marketers should use them is often clouded by vague recommendations, niche anecdotes, and buzzword mania.

The confusion has also impacted marketing analysts. More than ever they are facing questions of what can be measured and how. But very often there is neither a clear business goal nor action plan behind the question.

In order to select meaningful analytics for Facebook, LinkedIn, Twitter, blogs and videos, the key (as always) is to start with the business goals that your company is pursuing with each social media marketing effort.

But, as Jim Novo pointed out months ago, your team must come clean on what these business goals really are.

  • For example, just because you are blasting out messages on Twitter doesn’t mean that you are really doing viral or social marketing. You are just running a reach and direct response campaign much like any other form of spam or PR.
  • In that case you should also measure success with very similar metrics to those used for spam and PR, as Jim pointed out.

While there are wonderful lists of available metrics for social media overall, I didn’t come across a list yet that is grouped by the various business goals companies may be pursuing with their social media campaigns.

So, therefore, here is the grouped list that I would like to encourage.

Business Goal Description Typical Key Metrics
Brand advertising Even though the biggest opportunity with social media is thought to be in facilitating conversations, it is obvious that many marketers are still approaching social media in a way that is more similar to traditional advertising or PR. Companies doing this should then look at typical advertising metrics to measure and improve success

  • Reach and frequency, e.g. unique users and views of your Facebook application or Twitter followers
  • Engagement, e.g. number of comments or links on a post.
  • Share of voice
  • Quality of the audience that you are reaching, e.g. demographic fit
Direct response advertising Still with traditional marketing methods in mind, marketers often post tweets or blog articles with the goal of triggering a direct response, e.g. a registration to an event or an alert to a current promotion

  • Click-throughs
  • View-throughs
  • Outcomes, e.g. conversions, revenues, ROI.

Viral marketing The opportunity to increase the reach and effectiveness of your marketing messages through viral distribution represents both the most exciting and also the most challenging aspect of social media. The networked nature of social media makes them ideally suited for viral multiplication effects. Companies that know how to facilitate conversations and how to build their brands through the voices of their customers stand to build the best brands.

  • “Virality”, e.g. re-tweets on Twitter, application invitations on Facebook, or pick-up of your marketing messages across the blogosphere
  • Social graph of visitors reached by your effort, e.g. the number of their friend connections
  • Sentiment
  • Context of the conversations

Focus group It is often said that: “On traditional media you can shout but you cannot listen. On social media you cannot shout but you can listen.” Marketers that take this idea to heart may think of social media as a giant focus group that provides a window into the hearts of the market place and customers.

  • Volume of chatter on various topics, marketing messages, ad campaigns, or competitors that relate to the company’s business
  • Sentiment
  • Context of the conversations

Customer service Some social media channels, especially Twitter or blogs, provide the opportunity to respond or comment directly to the individuals that posted an article. This opens up the opportunity to encourage and thank fans while reaching out to help customers that are in need of help or feel disgruntled.

  • Customer cases handled
  • Improvement in customer satisfaction or net promoter score

Social CRM The opportunity to make social marketing personal extends beyond manual customer services. Namely, there is an opportunity for interactive marketing. Social media are part of the interactions and experiences that individuals have with your brand. It is commonly accepted that marketers should listen to their clients so that they can be relevant in their communications instead of interrupting with untargeted messages. As such, individuals’ interactions with your brand on social media represent another great channel for listening to individual customers and taking their interests into account.

  • Topical keywords that relate to an identified individual’s posts on Twitter, blogs, etc.
  • Topical keywords that relate to the posts with hyperlinks to your website from which an individual has clicked through to your site
  • RFR (Recency, Frequency, Reach, i.e. social graph.)

The overview reveals that social media measurement require combining data from multiple sources:

  1. Typical web analytics metrics such as unique visitors or views, click-throughs, and outcomes such as conversions, revenues, profits.
  2. Data about social media participants such as their demographic profile or number of friend/follower connections. This information would typically be available from the APIs of social media platforms or from social media monitoring solutions
  3. Social media monitoring trends such as the volume of chatter around specified topical keywords as well as sentiment

If you are a Unica customer, ask your account manager for our technical paper on how to measure metrics such as the above using Unica NetInsight and social media monitoring solutions.

Announcing: Free Optimization Wizard for Paid Search (PPC)

This wizard is for any marketer looking to get more results from their search engine pay-per-click (PPC) campaigns (and who doesn’t?).

It walks the analyst through a series of steps for increasing results, e.g. by eliminating wasted spending, identifying missed opportunities, improving the persuasion process, or optimizing budget allocation.

Web Analytics Question Support System

Click here to start the wizard


Bird's eye view of this wizard
Click here for a bird’s eye view summary flow chart

The wizard is the second example of an expert system that aims to help web analysts with their complex work. Just at the beginning of this month I had released the first wizard, namely for troubleshooting a drop in conversions on a website.

Couple comments and observations:

  • Just like a clinical decision support system isn’t meant to replace doctors, this wizard has no way of replacing the need for experienced web analysts, search marketers, or helpful consultants.
    • Doing the optimization still requires significant time and attention.
    • The wizard is just like a good adviser that has helpful hints but won’t do any of the work for you.
  • While releasing the troubleshooting wizard I had been wondering whether the idea of an expert system would lend itself to problems that aren’t “troubleshooting” in nature but more of general “optimization” nature.
    • It turns out the idea makes total sense for optimization as well.
    • But you can easily see a big difference if you compare the bird’s eye view of the PPC wizard vs. troubleshooting wizard. Namely, the latter is a decision tree whereas this new one is more an exploration of various optimization areas.
  • I still highly recommend the use of automated paid search management solutions such as SearchForce or Marin software. But if you review the wizard you will see that many areas for optimizing paid search involve tasks that cannot be automated.

I am not an SEM myself. So, this wizard will only become truly exciting with the help of user comments that can be added to any step of the wizard.

Look forward to hearing what people think and hope that this proves helpful.

If a tree falls in a forest and no one Tweets it, did it happen?

In hindsight, my colleague @benmnorth saved our face at Unica’s annual customer conference, “MIS”, which was held in Paris last week.

Ben’s leadership aligned us behind a common hash tag (#unicamis) for the conference. A big screen station running TweetDeck was set up in the coffee break area. And, thanks for these, the conference “was tweeted”.

Now, I had admitted my own difficulty with saying anything useful in 140 characters earlier. And, I don’t know how much the marketing professionals in attendance gained from the tweets.

But the following small anecdote opened my eyes a bit.

A little Twitter success story

The closing keynote was by Forrester’s Christine Overby. She had many great comments during her presentation including the following that was irresistible to tweet:

customer intelligence to become the molten core of marketing“.

So, this became my one “good tweed” done for the conference.

Next day, I am on the phone with Forrester’s John Lovett in far away New England to learn more about his upcoming webcast in regards to next generation web analytics.

And to my surprise …

He had already picked up his colleague’s quote from Twitter and found it to be a good fit to underline one of his points in his slides. Meanwhile, other industry observers from Boston to Singapore re-tweeted the quote as well.

From one person’s mouth to the twitterverse and back into the real world.

The moral

Of interest was not only the viral effect here.

But being that the re-tweeters were often industry influencers (e.g. analysts) themselves, this was just a small reminder that social media are no longer really a choice but a necessity.

In this case, tweets have become a metric for engagement.

Like all engagement metrics, volume and content of tweets are not a perfect measure.

But if there hadn’t been any tweets, worldwide industry observers would be excused to wonder whether the conference was not worth a Tweet, or attendees weren’t up to the Twitter.

When in fact, attendance was up 50% over last year, and many of the cutting edge customer presentations on online and offline integration had me sitting on the edge of my seat.

So, tweet it, just tweet it.

Thank you Ben!

Online-Offline Integration for Retention Marketing

(This post is part of a series on the state of multichannel metrics today, one year after the book came out.)

In a subscription based business model, e.g. mobile phone service, you have two ways to make a customer:

  1. gain a new one
  2. renew an existing one, i.e. retain them

When Unica’s clients from the mobile phone carrier industry report about their work they invariably start by describing how vital #2 is to their industry.

The market for mobile phone services is so saturated that the only way to gain a new client is to take them away from a competitor.

Sounds like a place for marketing innovation.

A few innovative Telcos have hit on ways to combine online and offline worlds in order to improve their success rate with retention marketing.

As I learned from one of my colleagues last year, here is how one company went about it.

Online-offline integrated analytics for detecting attrition signals

At a large US mobile phone carrier, traditional retention marketers were working on predicting which customers were about to leave for the competition. These clients would be included in retention marketing efforts.

Originally, the statisticians had been going after this job the old fashioned way, i.e. trying everything from a customer’s contract details to transactions (i.e. usage) and demographics details to find something that would predict attrition.

But the only variables that showed any influence were the age of the subscriber’s phone device and the amount that they paid on the last bill.

Not exactly enough to catch someone in the hot act when they are about to walk out through the door.

Yet, it was going OK.

To put it in numbers, the marketers were able to reach 70% of customers at risk of leaving by contacting 40% of the possible audience. So their predictive models were giving them some amount of lift.

But wait a minute … If someone is thinking about switching would they not likely be coming to the web site and doing something on there that deviates from their usual click behavior?

Might they not be checking available promotions or upgrades or ways to strike a deal?

The idea seemed so promising that the statisticians gave it a go.

They took a chunk of historical web data for registered clients. They paired that up with the same customers’ historical churn data in order to train a predictive model (along w/ the offline data).

And what they found was impressive

Indeed there were predictive click behaviors on their web site but it wasn’t intuitive.

  • Clients on a low subscription contract would have one kind of online signal that revealed their intention, e.g. address change.
  • Clients on a higher rate plan however turned out to send a different signal with their clicks.

The numbers rewarded them.

Now, when contacting 40% of the potential list they were able to reach an extra 15% responses for a total of 85% of potential responses.

That doesn’t just means lots of stamps and mailers saved.

It means foremost saving the cost of special discounts that they would have extended unnecessarily to clients who weren’t thinking about leaving anyway.

Highly worthwhile.

Real time?

Most of the online-offline integration case studies that you may have read about in this series were of interactive nature, i.e. online click behavior would prompt action within a short period of time.

Here we have an example of how a company first took a historical chunk of data to train their model. No real time needed here.

But now that the model has been trained, fresh web analytics data would be fed to it regularly in order to keep predicting current customers at risk.

The morale

This is yet another strong business case for integrating online and offline analytics.

No wonder the case is strong. After all

  • The case for competing on analytics is strong.
  • The case for using behavioral data is strong
  • Click data is a rich lather of behavioral data

It is time for the lollygaggers to stop acting surprised and jump on board!

Online to Offline cross-sales in retail banking

(This post is part of a series on the state of multichannel metrics today, one year after the book came out.)

The previous post focused on a travel company that listens to their customers’ online behavior so to get their cross-sales – or last minute – offers to those who are most likely to care.

Now how about the retail banking industry?

Retail banks and credit card companies have been great innovators in the use of analytics for direct and relationship marketing. For example, the case of CapitalOne is well described in the book Competing on Analytics.

For good reasons:

  1. Banking is a relationship business.
  2. Banks know embarrassingly much about their customers based on all those transactions and other data
  3. And what is the profit from a new bank customer at the moment when they first open their account? Negative, probably, until over the life time of the relationship the bank makes back their initial costs (and then some)
  4. Banks have learned that they are most successful with cross-selling products to customers within the first 30 to 90 days of the relationship. After that, customers seem to go on auto pilot with their relationship.
  5. Banks also have learned that new customers are most at risk in the beginning of their relationship and may spring back to their previous bank if something goes wrong.

So banks plan out all their customer communications very carefully by predicting which offer or message sent to which customer at what time is most likely to amount to maximized net present value.

(You might joke that we wouldn’t have the stupid mortgage crisis today if the direct marketing departments had been in charge of their banks)

So why is it then that many banks are such laggards when it comes to online offline integration?

Few industries have it easier.

  • You visit your bank’s web site frequently
  • You are almost always logged into your account when you go to your bank’s web site.
  • There is a big incentive for not deleting your cookie so that you won’t have to go through all those annoying security questions to “register” your computer.
  • Quite likely you even clicked the “remember my user ID” option so that even the bank’s home page greets you with “Hi Joe, welcome back”

All your bank’s products are outlined online so you have it easy to answer your own questions.

Looking for a car loan or savings account?

Likely you check rates online.

So … hellooo … is anyone listening?

Customer 1:  European bank cross-sells savings accounts

It seems a no-brainer.

The bank, with the help of a nifty online marketing consultant, mined their web analytics and customer data for clients who

  • have a checking account
  • but no savings account
  • YET who have recently been on the web site looking at savings rates.

All it took was a feed from web analytics looking at web pages relating to savings accounts and keyed by login-name of customers.

For extra credit, they could have extended the campaign to those who weren’t logged in but whose cookie was previously registered during an authenticated session.

According to the consultancy, the campaign was easy to do and very lucrative. So they are expanding the program.

Customer 2: Stock brokerage looks at web data to cross-sell options-trading

Another no-brainer.

Options-trades are a great way for an online stock brokerage to increase transaction volume and to lock in clients into a tighter relationship.

But options are risky and somewhat more complicated than trading stocks. So they aren’t everyone’s cup of tea.

Who is ready to receive the cross-sales offer?

Could it be those clients who are not yet authorized for options trading but who have recently been on the web page studying the process of how to sign up for options trading?

You betcha!

So what are the couch potatoes waiting for?

Legitimately, banks want to make sure that they stay within the accepted norms for privacy. The online-offline integration feels very new to them. So bankers are quick to throw up their arms and say that their hands are tied by the privacy rules of their organizations.

Are banks really that concerned about our privacy though?

Every night banks crunch through our daily account transactions to watch for unusually large deposits so that they can quickly bring us a cross-sales offer before we move the money elsewhere.

How is that for privacy!

Personally, I think that some of the arguments that we hear today are similar to what happened when the first train came out. Namely, it was said that traveling at the never-before-heard speed of 20 MPH was not healthy for human beings!

No doubt, we will see more banks review the opportunities very carefully. Innovators are already tapping into the integrated data. Others will follow.

In some future edition of Competing on Analytics we may well hear about some bank that rode the opportunity out to their advantage.

Online to Offline Cross-sales in the Travel Industry

(This post is part of a series on the state of multichannel metrics today, one year after the book came out.)

The previous posts focused on companies accelerating conversions from online to offline. Here now comes an example of cross- or repeat-sales. This time from the travel industry.

The company is Collette Vacations, a provider of global travel and escorted tours to more than 150 destinations. 91 years old, the company is far from old fashioned.

Other than their multichannel approach to marketing, what does Collette have in common with the previous three businesses that we examined (automotive, B2B, and real estate)?

All 4 examples are in the category of highly considered purchases. I.e. Collette’s tours to Antarctica, or Oberammergau aren’t something you book in a rush. Much more typical is that customers research their options online, watch available videos, sign up for a live presentation, and eventually book after clarifying all their questions, maybe by email, chat, or phone.

Last minute travel

Now, something that I learned from Jukka, at The Mileage company, is that travel business is very tricky business.

You wouldn’t guess from the outside.

But one of the many tricky aspects is that travel products are perishable goods just like tomatoes at the grocer.

You can’t sell a hotel room one day after it has been standing empty.

So what to do when Collette has vacation seats to Barcelona on sale and they need to find buyers quickly?

Should they spam their entire email list as a marketer would be tempted to do? Collette thought better.

Protect the future value of your email list

Email marketing is tricky business too. Email too often and while initially you may get results, eventually you burn the attention of your recipients. After all, except for cases when a tour sells out completely, there would always be last minute sales to promote.

If you were a spammer you would find reason to send spam every day. Yet, your future emails would likely remain unopened or go into the spam folder.

So, a year ago, Collette decided not to fall into that trap. Instead they connected their web analytics with their email campaign management system.

When, for instance, Barcelona vacations are on sale they have targeted the announcement to the segment of web site users that have recently spent time browsing web pages related to Mediterranean vacation options but haven’t recently been purchasing travel.

Not surprising that this segment is much more likely to care about the promotional announcement than the average population.

The sausage making

But how to connect web site visitors to their email addresses?

Collette’s web site permits registering online in return for something of value, e.g. the ability to save a wish list of vacation destinations. Along with online registration, it is best practice to save the login (or persistent cookie) that is created in conjunction with the provided contact information.

That info forms the basis of being able to listen to an individual’s clicks so to know better about the kinds of vacations that they may find of interest.

As Collette’s privacy policy states, customers have many options to opt-out. But if they do remain opted-in, “Knowing how you use the site enables us to better tailor our content and services to most effectively suit your needs.”

The Results

The official case study with further details on Collette’s implementation is available for download. Among some of the results that Collette shared is that their flagship, “welcome” campaign performs 30% above industry average.

The Morale

The hardest thing about this is not at all the technology in my opinion. But it is for the business to come up with ideas that entice visitors to register with their accurate email information. What value are you going to provide to your clients so that they will give you the email address where they actually do check their messages?

And since cookies are deleted eventually and people use multiple devices to browse the Internet it isn’t even enough to get a registration only once. Rather, the business needs to entice visitors to login periodically so to keep the data trail alive.

One would wish this was easier.

But what I like about this challenge is that it keeps marketing real. We have to provide value to the customer for the permission to include them in our analytics and the permission to communicate.

Two-way value has always been the basic ideal behind CRM.