Is Privacy dead, or just too hard?

Lorrie Faith Cranor and Aleecia McDonald from Carnegie Mellon conducted a study recently which repositioned the lack of online privacy as a time issue.

They reported “To read every [online] privacy policy you encountered in a single year would take 76 work days……”

So we all want our time online to be a more private affair, but find it impossible to wade through the policies and figure out what’s what? Further, even if you had the time to read them, would anyone but a Privacy Specialist understand them, and worse, be willing to forgo the benefits brought by Facebook and Google in an effort to maintain some sort of online anonymity? I suspect not in each case.

It’s hard to see how to solve this issue.

At a minimum it would seem appropriate to provide a simplified privacy policy, which would at least encourage consumers to become familiar with the terms they are signing up to. Controlling what your cookies are used for may also be key, Personalisation, yes, targeted advertising, no.

Over time I worry that the role of government will be to reign in on the issue if left unsolved, which would be a bad outcome for all.

Google Analytics – Top 3 Features for Ecommerce; A Digest

This post was written by Boris Gefter – freelance Acquisition Guru and consultant to 57 Signals.

Google analytics (GA) is rubbished more often than not by Omniture diehards and hardcore data analysts. They bleat persistently about their inability to feed GA with non-standard data (outside the scope of what the javascript captures) and readily extract the data (in the way you can with a data cube). But these guys are locked in time, probably still awaiting the arrival of the iPhone 3!GA has evolved in a fantastic way over the past 3 years! In its evolution it has made available rich data to those that care to harness it. But what is more impressive, is how easy and intuitive it is to use the interface and find answers to questions a sophisticated online store owner may ask. But, let me curb my Google appraisals for the time being, lest this blog post be censored by the powers that be. 😉

Jumping right in, here are my three favourite GA features (and there are many!)

1. Google URL Builder.

A humble servant of GA’s ability to capture and store url parameters. It is surprising how many people do not know that this functionality exists! The standard user will be used to viewing the “Traffic Sources Overview” report, but when you want to know what campaign, keyword, ad or placement on which network and partner has resulted in a sale, coding your own unique URLs could not be easier. Then, when it comes to retrieving this information, you can rely on your friend ‘Custom Reporting’….

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2. Custom Reporting:

The humble tab that sits atop the interface is the key to unlocking analytics glory. For those that know and love pivot tables and data cubes, GA has a gift for you. For those that are new to looking at dimensions and metrics, they key is not to be intimidated by the blank canvas. Start playing around, adding metrics (things that are measurable) such as time on page or conversion rate (if you have ecommerce tracking enabled) is really easy. Dimensions (what describes the data) can be configured to retrieve information that you coded into the Google URL builder in step two, by adding “Source” and “medium” alongside the metrics you are interested in.

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As an example, say you wanted to find out how successful your google adwords campaigns are (which you had already coded with the url tool, as seen above), you can simply add source as one of your dimensions and the relevant metrics such as visits and number of transactions as shown in this example. Then, you can filter by the source code which you coded in your URL tool.

The key, is figuring out what question you want to answer first, and then what sort of information will help you answer that question, then validating any data using common sense!

3. Conversion Segments/The Repunzel Report:

What if I told you that you were potentially losing out on more than 50% of your revenue by under-investing in a particular form of advertising. Wouldn’t that be valuable? This is where the “Conversion Segments” or “The Repunzel Report” as I have dubbed it (due to the fact that it is hidden in the top left corner of the analytics tower) becomes extremely valuable.

First let me assist the budding princes willing to use this report. You need to have ecommerce tracking enabled and implemented correctly on your site, then you can make your way into the conversions tab>multi-channel funnels>top conversion paths, then navigate to the top left section of the page to find conversion segments. Simple, right?

Now that you have found it, you can filter the potential traffic sources by first and last interaction. Whilst, the philosophy of attribution can be a prickly one, I like to refer to reports such as these to understand where advertising money is going and how much impact it is having.

What you can see from the example below is that paid advertising on a “last touch” basis, is reporting $140k+ worth of revenue, whereas on a “first touch” basis (where the value of the transaction is attributed to the first channel that brought the customer to the site in a default 30 day window) there is over $220K+ worth of revenue to be had. Now imagine that you are only spending $100K on advertising, thinking that it is only bringing in $140K, when, if you look at your conversions through the “first touch” lens, you can see that there is potentially more value to be had from your advertising dollar!

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I often like using first touch attribution to model the efficacy of acquisition channels because it is simple, and usually rather effective. This model can become complicated by things like remarketing and more diverse marketing channel portfolios. But, hopefully, this report will, at the very least get you thinking about the complexity of multichannel advertising interactions and spark a discussion about what is the right approach for your company in modelling and tracking conversions.

As much as I love diving into data and exploring new features of GA, I am always weary of tempering my enthusiasm to extract findings with solid statistics, common sense and other analytics tools (where possible). Having noted this, it is very easy to become intimidated with analytics tools and software. Which is why, often there is no substitute for simply getting your hands dirty with what tools like GA have to offer. I hope this post helps to make some of the less accessible features of GA more manageable.

What’s a great product without great service?

It’s rare that a great product would win without the support of great service, so why then are the two so quick to grow apart?

The problem, I think, is success.

Scale and its associated economies support the development of a product  but rarely do they support the development of the accompanying services. There are exceptions, of course, but not many; McDonalds is one, Apple another, Sadly I’m at a loss to think of a third.

It’s worth noting of course that Apple and McDonalds are are notable exceptions to the rule, albeit for vastly different reasons. McDonalds is a very, very large franchisor, and the “product” being sold does not come in a bun, the product is the Franchise. The Franchisee buys a proven recipe for fast food and efficient service. If McDonalds didn’t have control of the entire McD’s ecosystem through a tightly wound Franchise Agreement it would be impossible to maintain its brand of high-margin consistency that allows it to continue selling to franchisees at a premium.

Apple, on the other hand, is all about brand, and that brand extends through the product supply chain to the lifestyle, which includes the process of purchasing and ownership. Prior to Apple seizing control of its supply chain the service part was delivered by 3rd parties, now it is a powerful pillar in the house of Apple.

When a typical business grows, investment is poured into improvements in the production process, reducing the cost of goods and improving margins. The same can’t be said for service, great service at scale is costly, and returns to scale are minimal. In addition, training great service to new staff takes time, so the gap between product uptake and service delivery can grow rapidly if the growth was sudden and unforseen.

Improved margins are seductive, investments in service are not, and so the conflict begins.

As a business owner, you can get ahead. At a minimum there should be a record kept of a consistent service KPI such as Net Promoter that can serve as an early indicator of customer sentiment taking a turn for the worst. Where growth is happening at the expense of service the growth should be arrested until the issue is identified and resolved, hard as it may be to do so.

Positioning your entire business as a product is smart, have a McDonalds-like operating manual with detailed descriptions of service procedures and quality standards, or emulate Apple by asserting service as a key part of your brand, then live it with every touch-point!

To favour growth at the expense of service is a short term win, the positive sentiment that propelled growth in the first place is already evaporating, allow that to continue and chances are your brand will never recover.