Some people believe they can legitimately improve the conversion rate of visitors who came to their site and left without converting. Everyone is spending money on remarketing nowadays. Let’s deconstruct a live example while I’ve got your attention.

Why is Remarketing Valuable?

Consensus building statements include:

• they’ve been to our site, they are more likely to buy – just look at return visitor conversion!
• with a good enough offer, they’ll convert!
• it creates awareness (if not firmly convinced of measurable economic value)
• we’re making 20x ROI on view through revenue! (why isn’t revenue up?)

1. Their conciliatory messaging – ‘still offering great rates’. Is this because of their reputation as a high cost carrier, or them knowing the proximity to my trip based on my search? It’s a bit of a mixed message, but I liked its wholesome spin, or lack thereof.
2. Nice job with the origin location (DIA)
3. It’s dead simple – really.

I’ve never spoken to them.

Our sales guy has reached out to them, but with little success.

I bought from them 2x – but I’ve browsed the site 100′s of times. I love the outdoors and think they’re doing a great job, although  their average displayed price seems to creep up month after month after month, making the real ‘deals’ harder to find? Maybe they are trying to trade more inventory for higher prices? Could you measure that potential impact on loyalty? I don’t know…if I begin to think a site is just stocking product I could find elsewhere under the guise of a deals site, yeah I’d probably visit less frequently.

In any event, note the screenshot below – The caption could be – “Do I still need my product page?”

A challenge for a deals site is not having a full stock of all typical shoe sizes. Initially, they began offering sorting and filtering functions, even creating category pages where the category was some combo of “Gender + Shoe Size Range” such as [Male 10-13]

Now, when you hover over a shoe, the function displays all of the available sizes…so those Zoot Tri shoes you know you like and don’t need to read about can be added to the cart, size and all from the product page. I think it’s great.

But once again, while this obviously improves the experience – it introduces measurement challenges. What about my precious funnel?

[Logged in > category > product > checkout > order]

I’d be curious to see whether product pages per visit with an order is driven down, when you segment on shoe purchases. Maybe it won’t even move the needle numerically, but at least it’s a good idea! Simple is good.

Across other industries – on-hover can add tons of detail to a simple listing on a category page. Hotels can post reviews, pricing, other packaged offers, etc…and the person need not visit the actual hotel page. It’s a much more compelling case in retail, obviously since the purchase threshold is lower and people may or may not know what they want. What about pick-up in store, like ToysRUs.com? The options are endless for innovation on the category or sub-category template.

Gotta run,

Jeff

” Modernity provides too many variables, but too little data per variable. So the spurious relationships grow much, much faster than real information.”

Variables are what we analytics professionals call measures or numbers. Sales, conversion rate, average value, etc…But as our ability to collect, store and query this data improves, so does our ability to create new variables and new dimensions. Look at a typical marketer’s data toolkit – not only do they have to come up with all these metrics and dimensions, combine data from multiple sources, tools and processes….but they need to act!

The signal grows, as does the noise.

How can anyone make any sense of it all? Here are some guidelines we’ve developed after working with tons of data across decades of internal experience here at Delve – this pertains primarily to B2C clients, focused on making marketing decisions to both acquire new customers and retain existing ones:

1. Only use predictions that make sense – if an algorithm tells you to do something counter intuitive, use your brain.
2. Use a few critical dimensions, throw out the rest. Loyal customers vs. First time buyers – that’s a good distinction. 3 time buyers vs 4 time buyers, who cares.
3. Focus on optimizing traffic sources based on a single metric – conversion to a first time buyer is a great one for most growing SME’s. Larger businesses have different protocol but may be too steeped in bureaucracy and poorly designed incentives to make any optimization progress.
4. Don’t rely too much on A/B testing, instead focus on user experience testing, common sense and fast/optimized web experiences.
5. Collect feedback from your customers – integrate feedback solicitation mechanisms into the browsing experience AND post-purchase experience. Avoid overly structured surveys from big companies claiming you can benchmark satisfaction across industries, blah blah blah. Find problems, get free-form feedback and act.
6. Visualizing data rocks, but if a simple table in Excel will do, use it! Fancy doesn’t get you points…focus on making decisions.

Last but not least – USE A NULL HYPOTHESIS. Changing things for no reason is a crime many marketers are guilty of. Always say to yourself…”what’s wrong with the way things currently are”. If you can’t really concretely answer it, I think you’re barking up the wrong tree.  Tiny adjustments can create big changes…be careful calibrating when dealing with leverage of any kind.

Thoughts?

Jeff

How many people came into the store today? Let’s see, the store has 3 entrances. If we count-up the # of people who came in Door A, Door B and Door C…this should give us a reasonable estimate of total unique visitors to the store, right? Kind of like a website where you can only enter once per visit. Sure, I can come back later through another door or on the web my session came timeout, but it should be reasonably close.

What it we tried counting by the # times people pass through various departments in a department store? Let’s take 5 people and the departments they visit:

• John – tools, toys, food, pharma
• Jeff – sports, clothing, food
• Joe – pharmacy, food, tools
• Jesse – register for gift card
• James - tools, food, sports

We know there are 5 people, but let’s try counting by way of department.

We see that if we sum people across departments we get a count of 14 people, where only 5 unique people actually exist. The highly sophisticated Venn diagrams below the table where the circles represent some dimension highlights both good and bad dimensions for summing unique items. The department example falls under bad (both for summing and artistic sensibility).

Who cares? Well, in a world where data is increasingly defined by having multiple dimensions associated with each metric there’s quite some room for this type of error or similar errors in aggregating data. If a # ever seems really high or skewed and you’re operating across many dimensions…ask yourself, can the item generating the metric live in many dimensions?

Other situations where summing unique folks across dimensions could get complex:

Geography – person could have many homes. Zip codes crossing multiple counties?

Retail – multiple departments. Multiple purchases (hopefully) or multiple unique customers in same household.

Finance – multiple cards or accounts.

Gaming – played multiple games. Unique person played the same game during multiple sessions on the same date.

Travel – multiple bookings same vacation.

The most infamous example of all at this point for marketers is SAME PERSON MULTIPLE DEVICES (ha ha ha laughs the distracted consumer, catch me if you can!). 

One,

Jeff

Bounce Rate – the % of visits, who having entered on a particular page, go no further than that page during their session. Note that on a global basis, this metric may not make much sense, since you can’t bounce off a site, you have to bounce off a particular page. In SiteCatalyst Version 15 the metric is now defined out of the box, but formerly it was determined by a calculation like:

Single Access / Entries – where single access meant a page was the first and last pageview of a session and entries means how many visits entered the site on that page.

EXAMPLE: Let’s say 1,000 people enter on my homepage and 150 never go any further. My homepage has a bounce rate of 15%.

About entries – since bounce rate must apply to a particular page, it only matters if you entered on that page. If very few people enter on a page and it has a high bounce rate, there’s probably very little to consider. But if that page has a lot of traffic flowing to it internally, you may want to check on….

Exit Rate – exit rate is sort of like bounce rate that doesn’t care about how you got to the page. It still relies on some page being the last page viewed within the visit session however. Here’s an example – let’s say I enter on the homepage then click on your Hiking Boots category page. I filter a few things then get to a pair of boots I like. I get distracted, close out my tab and take off. My exit was on the hiking boot product detail page.

EXAMPLE: Let’s say of the 1,000 people who viewed the product detail page today, 340 never viewed any pages afterward. That gives us an exit rate of 34%.

Further, let’s say that 300 people entered on that page and 100 never viewed any additional pages. Then the page would have a 33% bounce rate. But wait, 340 people never viewed any pages after the product detail page – true…So, are my bouncers also included in the exit rate calculation? Let’s recap:

BIG EXAMPLE: Some product page:

1000 views – 340 times the last page viewed in the session = 34% exit rate

300 entries – 100 bounces = 33% bounce rate

Is the 100 included in the 340?  Of course! Exit rate doesn’t care how the visitor got to the page, it only requires the page to have been the last page viewed in the session. In SiteCatalyst the calculated metric would be:

exits / visits = exit rate or the % of sessions which ended on some particular page. Again, exit rate for the site has even less meaning than bounce rate because any session that begins, must end.

THEORETICAL NONSENSE:

If a site has one page, can bounce rate and exit rate ever be different? Well, everyone enters on the same page, and you can’t go to any other pages. But, you can reload the page, did you technically bounce? The exit rate will be 100% for the page, since you can’t end the session on any other pages. So what about that reloading – does it get you off without bouncing? We’ve never done any web analytics consulting for 1 page sites, but here’s what Google says:

Single-Page Sites

“If you have only one page on your site (a blog, for example), Google Analytics doesn’t register multiple pageviews unless visitors reload that page. As a result, single-page sites tend to have high bounce rates.”

So there you have it – if the page is reloaded, the visitor didn’t bounce. So, the exit rate on the page will be 100% but the bounce rate could be zero percent if everyone who visits the site reloads the page.

PRACTICAL UPSHOT:

If you have a high bounce rate, make sure lots of people are entering the site before you worry too much.  If your visitors can accomplish their goals on that page, who cares about bounce rate. Our blog has a pretty high bounce rate on some pages because the post is read, then they move on. Thanks for reading!

High exit rates can make sense, especially on pages like your receipt page, or deeper into the funnel, eg the product detail or the preliminary cart pages. If the majority of your traffic doesn’t buy on the first visit, there may be nothing wrong here.

Most likely you want to keep an eye on these metrics as a signal, especially before/after or around site layout changes. Another way to use the metrics – segmenting traffic by behavior to improve online media spend. Affiliate traffic will probably have a pretty poor behavioral score but you’re only paying for completed goals. SEM should have a bounce rate higher than direct or organic in most cases but much lower than display. Now I’m generalizing.

Gotta bounce,

Jeff

The one drawback is that since most businesses operate on a day-of-week comp, their date range simply doesn’t compare Mondays to Mondays, Tuesdays to Tuesdays, etc..For example, 8/28/12 is comp’d against 8/30/11.

We actually did a study of several online retailers Google Analytics visits trended year over year, comparing the correlation between the day of week relationship vs the numerical one. The correlation coefficients were .9x for day of week and flat or negative for the numeric date comparison.

What business actually compares the numerical date year over year? I can’t think of one off the top of my head…

Time out,

Jeff

http://www.thestreet.com/story/11449653/1/the-10-richest-colleges-in-america.html?cm_ven=outbrain

Not the case – after a 50 word introduction, I the visitor was left to sort through over 11 pages of content! The column size of the actual content is barely larger than the columns dedicated to financial quotes and adverts. I don’t mind this trick when they offer the option to ‘view all 10′ or however many ‘top things…’ they’re discussing but it’s nowhere to be found.

Come on, enough with the crap it’s 2012 and you’re lucky to have anyone on your site. I realize it’s a link from OutBrain which syndicates garbage content across the web but what the heck!? I know you’re a public company and pageviews = dollars but at what cost? Maybe it’s all incremental…garbage top 10 lists that pollute the Internet for so long people actually believe they’re reading ‘news’.

In any event – what are some good examples of not forcing visitors through absurd content funnels with scant information? You know, like a 30 second ad to watch a 1 minute video?

• YouTube – most of the time you can skip the advertisement after 5-10 seconds. The longest forced ad is only 15 seconds and there appears to be a correlation between the asset length and the required ad duration before skipping.
• Any site that lets you immediately view all without dealing with pagination.

I’d like to see if pageviews per session actually increased. Perhaps this is throw-away content and retention isn’t an issue? How can you measure whether or not the impact of a bad experience is felt across time, over many sessions which may fail to materialize as a result? That’s not easy to answer, but the obvious choice is not to create such nonsense in the first place. As a rule, create more pages if you have more REAL content.

Click here to see my outro,

Jeff

Given they play in the ‘deep-deal’ space they are only accessing inventory that ‘has to move’. You can imagine it would be hard to get a solid stock of the most popular sized men’s and women’s sneakers and boots at all times for all products. It’s probably impossible.

So, knowing that footwear sells, but also knowing that the consumer doesn’t want to browse through a number of product detail pages trying to find what’s in-stock…make the size the primary criteria. Creative from an email today, above. Additionally, below – the category template allows for simple filtering of the 2 dimensions that matter most: gender and size. Note, most merchants split the page itself on gender…

This approach is also highly personalized without having to know the size of the email record’s foot. Self-selection personalization is just as good as 1:1 personalization, just less data-heavy. Try to think of ways to apply this reasoning to your own customer.

They key takeaway here is that the typical path to discovery need not begin at the traditional category type. Maybe the right point of departure is a bit deeper into the pattern. Additionally, when the initial interest is PRICE based (daily deals / deep discount), no need to always separate out men’s and women’s on the category level. Go deep…but go broad!

Some examples from other verticals:

• Travel – offer deals which qualify for special payment terms or financing offers.
• Autos – start with cargo room before talking miles per gallon.
• Dining – merchandise desert options/value before the entrees to get people in the door.

Don’t forget to look further down the criteria set in your consumer’s typical browse/buy pattern…you may want to reorder a few things from time to time.

Climb on,

Jeff

In the 60′s and 70′s the US underwent a ‘running boom’. Marathons became popular and millions began running. Of course, this led to increased demand for shoes. While serious athletes had been wearing/racing in running flats for sometime, the average runner was not quite durable enough for such a spartan sole.

As you’d expect, US shoe manufacturers began producing more cushioned running shoes, with an elevated heel and stabilizing insoles to offset pronation or supination (feet rolling inward or outward on ground strike). If you never gave much thought to running form, this was your best bet to avoid injury and have a relatively comfortable run. Why the elevated heel? Well, because people tend to strike heel first without knowing any better. I did for 10+ years. Most elite runners do NOT heel strike, since people have been running.

THE SHIFT:

A book called, ‘Born to Run‘ by Chris McDouggal which chronicled the ultra-marathons of some tribes in Copper Canyon, Mexico, spurred what might be called, ‘the barefoot running revolution’ . The Copper Canyon tribes did NOT run barefoot, oddly enough. Runners of all experience levels began wearing Vibram Five Fingers (toe shoes) and the Nike Free became incredibly popular. Runners also began trying to shift their landing zone from heel to mid-foot or the ball of their foot. Some of the perceived benefits:

• Be more like the crowd (most important and ridiculous)
• Ankle is a weak link, landing on heel exposes weak link while the mid-foot strike = more elasticity and energy return (legitimate, but a tough physical changeover for most). This is well understood and true.
• Better ground feel – they even came up with a name for it, http://www.bio-medicine.org/biology-definition/Proprioception/. This really depends on the surface you’re running on.

RUNNING SHOE INDUSTRY REACTION:

The initial industry reaction: Brooks and New Balance initially resisted the ‘fad’. (2009′ish).  Big companies with established market-share don’t like having to re-engineer their products, especially when they’ve been working well for decades with slow and predictable upgrade cycles. Colors change sometimes! People switching from running to cycling was more of a threat than people changing ‘how’ they ran.  Would this move confuse current customers during their repurchase phase(s)?

http://talk.brooksrunning.com/2010/01/25/barefoot-running-an-open-letter-from-brooks-ceo-jim-weber/ (Brooks CEO on demerits of running without shoes)

Companies such as Newton Running and Inov-8 began to emerge from relative obscurity as people became more aware of running form. Asics only very recently came out with a Nike Free knockoff (2012) as they lost their #1 spot to New Balance in the running shoe segment.

PRESENT DAY:

Companies such as New Balance have gone sofar as to recruit people resembling Jesus that live in Boulder, CO to help design shoes that aren’t really shoes at all…just glorified racing flats. (see below – a very talented runner but this is a horrible idea for most people who weight more than 130 lbs). I’d say anything is more certainly better than barefoot.

Some creative from the New Balance site below:

Not to chase trends, eh? Why do they need mathematical operators?  As a person who has run injury free over the past 12 years, changed to a more midfoot strike but has NOT gone to a minimalist shoe I’ll gladly expose the hype. A minimalist feel means you will get really screwed if you step on a huge rock while trail running, additionally you don’t have any cushioning in the shoe to reduce impact absorption on your joints.

Unless you’re extremely light or have been running with flats productively for years, (think professional distance runner) you NEED some level of cushioning. There may be some merit to walking around in flats (they need not be $100) to strengthen your feet a bit if you’ve been wearing high heeled shoes with inserts for years….but running on rocky trails in flats…come on guys and girls.

Companies such as Newton Running reduce the height difference between the heel and toe of their shoes in order to promote a more mid-foot strike, without cutting back profusely on cushioning. I like Newton shoes and they did help me sort out my running form without hurting myself on too minimalist a shoe.

THE ANTITHESIS:

Hoka One One. What?

Yes, maximalist shoes. A European shoe company has begun making a splash with ultramarathon runners here in the US. These shoes have nearly 3x the cushioning of a traditional trail runner and probably 5x or more that of a minimalist trail shoe. I’ve put about 80 miles in a pair and they are quite comfortable. They’re not my sole shoe, but I do wear them about 1/3rd of the time. They do have a very low heel to toe drop, the same as the New Balance Minimus line, 4mm. Note that smaller foot sizes may have an exaggerated heel/toe offset due to basic geometry.

SO WHAT? (food for thought)

• What’s the pivot point that’ll fundamentally shift consumer perception of your product, in your industry? A book about runners in a canyon?
• Is what you’re currently doing encouraging safe usage or might your customers be developing bad habits?
• Do your customers need some new good habits that you can proactively introduce? (real of ‘feel good’ habits)
• If a new preference is emerging, how do you avoid bucking the trend while not destabilizing consumer repeat purchase patterns within existing product lines?
• If the product cycle is changing quickly and even the big players have entered the new trend, is there room to go against the grain for some small sub-set of the market that may reach back into the broader market (think Hokas)?
• Can one company service ALL preferences within the market and still understand their core customer?
• Do threats come from within the existing product or from product substitutes (running vs cycling)?

PRICING & OTHER INDUSTRIES:

It’s relevant to note that Newtons, Hoka and other specialty running shoe manufacturers charge quite a premium. Newtons run between $150-$175 as do Hokas. New Balance Minimus line shoes are well over $100 even though the amount of material used is less than half that of their legacy stability/motion control shoes. They are getting more and giving less while telling you quite clearly you should be excited about receiving less, because it’s good for you. While I can’t think of any one situation that quite parallels this one step-by-step, I’ll throw out a few:

• Hybrid cars – horsepower per dollar traded for miles per gallon. Automakers must produce to avert market-share losses and preserve loyalty. Interestingly enough, Honda, while having several Hybrid and Electric vehicles still does well with the Civic and new Fit models simply because they’ve squeezed the most possible ‘fun’ out of small 4-cylinder motors using innovative engineering (V-tec comes to mind, dual overhead cams, etc…). I can’t comment on margins across these scenarios, but I’d imagine they’re fairly even given the burnt out consumer as of late.

• Travel Price/Rate Discovery- several years ago, mainly driven by cheap or free API access to hotel and flight pricing, a new breed of travel site began to emerge: the meta-search engine. Kayak.com and Sidestep.com were the leaders…Kayak survived (the brand anyway). They effectively replaced the Online Travel Agency’s search function and also created a much improved user experience for accessing maximum price information as quickly and easily as possible. The consumer got better price discovery and the OTA entered a hyper-competitive world which they’re still entrenched in. Search engines want their ad dollars and Hotel companies want reduced margins and to steer consumer demand their way directly. An interesting point is that Kayak’s proper name is ‘Kayak Software Company’.

• Smartphones – what happened to Nokia? They had enough cash to develop models that were just as good as the first iPhone or Android rigs. Probably lots of discussions about how it was a fad, people can’t type on it, focus groups don’t like it, etc…whoops.

What’s next?

Jeff

Data Extensions are used to hold extra data which relates to a subscriber. The information is matched to the subscriber by a common field value. Using data extensions, we can relate data to subscribers which does not have a one-to-one relationship.

For example, the Exact Target subscribers list contains the information field Email Address. Suppose we wanted to have a list of all purchases made by each subscriber. We can first make a data extension containing email addresses  and customer ID’s. Then we can create another data extension containing customer ID’s and purchase information (Data, Item, Brand, Amount, etc.). The two data extensions can then be connected by a data relationship.

Data Relationships:

Data relationships are used to connect information between data extensions. From above, we had created two data extensions. One matching emails to customer ID’s, and the other listing purchase information associated with customer ID’s. Using a data relationship we can link the two data extensions.

Result:

After the data extensions are linked, we can pull data from the extensions to populate email content by writing AMP script calls.

AMP script is a scripting language that is embedded within HTML emails and text emails.The Exact Target system processes the script at the point where it is included in the email to render content on a subscriber-by-subscriber basis. Therefore, one HTML email can turn into many different personalized emails!

Andrew