Tag Archive | "Driven"

Adnan Ebrahim: Founder Of CarThrottle.com Explains How He Took A Video Content Driven UK Car Blog To A Multi-Million Dollar Empire

 [ Download MP3 | Transcript | iTunes | Soundcloud | Stitcher | Spotify | Raw RSS ] Back in 2008, I interviewed Alborz Fallah about his million-dollar car blog, CarAdvice.com.au. A teenaged Adnan Ebrahim listened to the episode and felt inspired. He wanted to start a car blog of his own. Despite his young age, Adnan […]

The post Adnan Ebrahim: Founder Of CarThrottle.com Explains How He Took A Video Content Driven UK Car Blog To A Multi-Million Dollar Empire appeared first on Yaro.Blog.

Entrepreneurs-Journey.com by Yaro Starak

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Google Profits Rise Driven By Increasing Ad Revenues

Google reported a 4 percent increase in profits for Q1, driven by a steady growth in ad revenues. The company was hurt by the recent strength of the U.S. dollar, however.

Home – SearchEngineWatch

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LinkedIn members are unique, driven and big spenders. . . or so they say

LinkedIn ReportLinkedIn just published a new study about harnessing the power professional consumers or “prosumers” as they call them. Without even looking at the numbers I can tell you that LinkedIn members have more buying power. It’s a networking site for people who are serious about whatever their business is, so chances are they have more discretionary income and a desire to advance – both professionally and personally.

What surprises me is LinkedIn’s choice of opening and closing graphics for their report. It’s a group of cavorting college students. The girls are all riding on the back of the boys and everyone is laughing.

Is this really LinkedIn’s audience? Shouldn’t we see people at work, at a conference. . . girls not riding on a guy’s back?

Let’s take a fact break:

  • LinkedIn members have 2x more buying power than Facebook members. They’re also loyal (86%) and 78% said they were willing to pay more for high quality items. That’s great news if you sell higher quality items – this is your audience.
  • LinkedIn members are aspirational. 76% are considering a long vacation, 66% are looking to buy a new car.
  • LinkedIn members are 2x more likely to trust information they read on LinkedIn compared to any other network.

Look where they go with that statement:

LinkedIn Content Chart

This chart rates various content sources based on worth and innovation. LinkedIn, Wired and Inc all do well on both counts. The Wall Street Journal, The New Yorker and The New York Times are worth reading but not all that innovative.

Facebook, however, sits squarely in the “Wastes My Time” section with a helping of “Less Innovative.” Oh, snap. Twitter comes off a little better but not much.

If that wasn’t enough of a slap, LinkedIn also put together a chart showing the uniqueness of their audience:

LinkedIn Unique audience

19.2 million monthly viewers on LinkedIn. 13% of those people don’t have a Facebook account. Which means the overwhelming majority does. 58% don’t use Google+ and here’s an interesting one, 83% of LinkedIn users do not visit Pinterest. You might think it’s because LinkedIn is more male oriented but they say it’s actually a 50-50 gender split. So I guess those driven prosumers just don’t have time for the fine art of baking, decorating and curating cool pics.

Bottom line, LinkedIn is an excellent place to communicate with upscale consumers, not just about B2B subjects, but B2C, too.

 

 

Marketing Pilgrim – Internet News and Opinion

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Experiment Driven Web Publishing

Do users find big headlines more relevant? Does using long text lead to more, or less, visitor engagement? Is that latest change to the shopping cart going to make things worse? Are your links just the right shade of blue?

If you want to put an end to tiresome subjective arguments about page length, or the merits of your clients latest idea, which is to turn their website pink, then adopting an experimental process for web publishing can be a good option.

If you don’t currently use an experiment-driven publishing approach, then this article is for you. We’ll look at ways to bake experiments into your web site, the myriad of opportunities testing creates, how it can help your SEO, and ways to mitigate cultural problems.

Controlled Experiments

The merits of any change should be derived from the results of the change under a controlled test. This process is common in PPC, however many SEO’s will no doubt wonder how such an approach will affect their SEO.

Well, Google encourages it.

We’ve gotten several questions recently about whether website testing—such as A/B or multivariate testing—affects a site’s performance in search results. We’re glad you’re asking, because we’re glad you’re testing! A/B and multivariate testing are great ways of making sure that what you’re offering really appeals to your users

Post-panda, being more relevant to visitors, not just machines, is important. User engagement is more important. If you don’t closely align your site with user expectations and optimize for engagement, then it will likely suffer.

The new SEO, at least as far as Panda is concerned, is about pushing your best quality stuff and the complete removal of low-quality or overhead pages from the indexes. Which means it’s not as easy anymore to compete by simply producing pages at scale, unless they’re created with quality in mind. Which means for some sites, SEO just got a whole lot harder.

Experiments can help us achieve greater relevance.

If It ‘Aint Broke, Fix It

One reason for resisting experiment-driven decisions is to not mess with success. However, I’m sure we all suspect most pages and processes can be made better.

If we implement data-driven experiments, we’re more likely to spot the winners and losers in the first place. What pages lead to the most sales? Why? What keywords are leading to the best outcomes? We identify these pages, and we nurture them. Perhaps you already experiment in some areas on your site, but what would happen if you treated most aspects of your site as controlled experiments?

We also need to cut losers.

If pages aren’t getting much engagement, we need to identify them, improve them, or cut them. The Panda update was about levels of engagement, and too many poorly performing pages will drag your site down. Run with the winners, cut the losers, and have a methodology in place that enables you to spot them, optimize them, and cut them if they aren’t performing.

Testing Methodology For Marketers

Tests are based on the same principles used to conduct scientific experiments. The process involves data gathering, designing experiments, running experiments, analyzing the results, and making changes.

1. Set A Goal

A goal should be simple i.e. “increase the signup rate of the newsletter”.

We could fail in this goal (decreased signups), succeed (increased signups), or stay the same. The goal should also deliver genuine business value.

There can be often multiple goals. For example, “increase email signups AND Facebook likes OR ensure signups don’t decrease by more than 5%”. However, if you can get it down to one goal, you’ll make life easier, especially when starting out. You can always break down multiple goals into separate experiments.

2. Create A Hypothesis

What do you suspect will happen as a result of your test? i.e. “if we strip all other distractions from the email sign up page, then sign-ups will increase”.

The hypothesis can be stated as an improvement, or preventing a negative, or finding something that is wrong. Mostly, we’re concerned with improving things – extracting more positive performance out of the same pages, or set of pages.

“Will the new video on the email sign-up page result in more email signups?” Only one way to find out. And once you have found out, you can run with it or replace it safe in the knowledge it’s not just someone’s opinion. The question will move from “just how cool is this video!” (subjective) to “does this video result in more email sign-ups?”. A strategy based on experiments eliminates most subjective questions, or shifts them to areas that don’t really affect the business case.

The video sales page significantly increased the number of visitors who clicked to the price/guarantee page by 46.15%….Video converts! It did so when mentioned in a “call to action” (a 14.18% increase) and also when used to sell (35% and 46.15% increases in two different tests)

When crafting a hypothesis, you should keep business value clearly in mind. If the hypothesis suggests a change that doesn’t add real value, then testing it is likely a waste of time and money. It creates an opportunity cost for other tests that do matter.

When selecting areas to test, you should start by looking at the areas which matter most to the business, and the majority of users. For example, an e-commerce site would likely focus on product search, product descriptions, and the shopping cart. The About Page – not so much.

Order areas to test in terms of importance and go for the low hanging fruit first. If you can demonstrate significant gains early on, then it will boost your confidence and validate your approach. As experimental testing becomes part of your process, you can move on more granular testing. Ideally, you want to end up with a culture whereby most site changes have some sort of test associated with them, even if it’s just to compare performance against the previous version.

Look through your stats to find pages or paths with high abandonment rates or high bounce rates. If these pages are important in terms of business value, then prioritize these for testing. It’s important to order these pages in terms of business value, because high abandonment rates or bounce rates on pages that don’t deliver value isn’t a significant issue. It’s probably more a case of “should these pages exist at all”?

3. Run An A/B or Multivariate Test

Two of the most common testing methodologies in direct response marketing are A/B testing and multivariate testing.

A/B Testing, otherwise known as split testing, is when you compare one version of a page against another. You collect data how each page performs, relative to the other.

Version A is typically the current, or favored version of a page, whilst page B differs slightly, and is used as a test against page A. Any aspect of the page can be tested, from headline, to copy, to images, to color, all with the aim of improving a desired outcome. The data regarding performance of each page is tested, the winner is adopted, and the loser rejected.

Multivariate testing is more complicated. Multivariate testing is when more than one element is tested at any one time. It’s like performing multiple A/B tests on the same page, at the same time. Multivariate testing can test the effectiveness of many different combinations of elements.

Which method should you use?

In most cases, in my experience, A/B testing is sufficient, but it depends. In the interest of time, value and sanity, it’s more important and productive to select the right things to test i.e. the changes that lead to the most business value.

As your test culture develops, you can go more and more granular. The slightly different shade of blue might be important to Google, but it’s probably not that important to sites with less traffic. But, keep in mind, assumptions should be tested ;) Your mileage may vary.

There are various tools available to help you run these test. I have no association with any of these, but here’s a few to check out:

4. Ensure Statistical Significance

Tests need to show statistical significance. What does statistically significant mean?

For those who are comfortable with statistics:

Statistical significance is used to refer to two separate notions: the p-value, the probability that observations as extreme as the data would occur by chance in a given single null hypothesis; or the Type I error rate α (false positive rate) of a statistical hypothesis test, the probability of incorrectly rejecting a given null hypothesis in favor of a second alternative hypothesis

For those of you, like me, who prefer a more straightforward explanation. Here’s also a good explanation in relation to PPC, and a video explaining statistical significance in reference in A/B test.

In short, you need enough visitors taking an action to decide it is not likely to have occurred randomly, but is most likely attributable to a specific cause i.e. the change you made.

5. Run With The Winners

Run with the winners, cut the losers, rinse and repeat. Keep in mind that you may need to retest at different times, as the audience can change, or their motivations change, depending on underlying changes in your industry. Testing, like great SEO, is best seen as an ongoing process.

Make the most of every visitor who arrives on your site, because they’re only ever going to get more expensive.

Here’s an interesting seminar where the results of hundreds of experiments were reduced down to three fundamental lessons:

  • a) How can I increase specify? Use quantifiable, specific information as it relates to the value proposition
  • b) How can I increase continuity? Always carry across the key message using repetition
  • c) How can I increase relevance? Use metrics to ask “why”

Tests Fail

Often, tests will fail.

Changing content can sometimes make little, if any, difference. Other times, the difference will be significant. But even when tests fail to show a difference, it still gives you information you can use. These might be areas in which designers, and other vested interests, can stretch their wings, and you know that it won’t necessarily affect business value in terms of conversion.

Sometimes, the test itself wasn’t designed well. It might not have been given enough time to run. It might not have been linked to a business case. Tests tend to get better as we gain more experience, but having a process in place is the important thing.

You might also find that your existing page works just great and doesn’t need changing. Again, it’s good to know. You can then try replicating this successes in areas where the site isn’t performing so well.

Enjoy Failing

Fail fast, early and fail often”.

Failure and mistakes are inevitable. Knowing this, we put mechanisms in place to spot failures and mistakes early, rather than later. Structured failure is a badge of honor!

Thomas Edison performed 9,000 experiments before coming up with a successful version of the light bulb. Students of entrepreneurship talk about the J-curve of returns: the failures come early and often and the successes take time. America has proved to be more entrepreneurial than Europe in large part because it has embraced a culture of “failing forward” as a common tech-industry phrase puts it: in Germany bankruptcy can end your business career whereas in Silicon Valley it is almost a badge of honour

Silicon Valley even comes up with euphemisms, like “pivot”, which weaves failure into the fabric of success.

Or perhaps it’s because some of the best ideas in tech today have come from those that weren’t so good. (Remember, Apple’s first tablet devices was called the Newton.)
There’s a word used to describe this get-over-it mentality that I heard over and over on my trip through Silicon Valley and San Francisco this week: “Pivot“

Experimentation, and measuring results, will highlight failure. This can be a hard thing to take, and especially hard to take when our beloved, pet theories turn out to be more myth than reality. In this respect, testing can seem harsh and unkind. But failure should be seen for what it is – one step in a process leading towards success. It’s about trying stuff out in the knowledge some of it isn’t going to work, and some of it will, but we can’t be expected to know which until we try it.

In The Lean Startup, Eric Ries talks about the benefits of using lean methodologies to take a product from not-so-good to great, using systematic testing”

If your first product sucks, at least not too many people will know about it. But that is the best time to make mistakes, as long as you learn from them to make the product better. “It is inevitable that the first product is going to be bad in some ways,” he says. The Lean Startup methodology is a way to systematically test a company’s product ideas.
Fail early and fail often. “Our goal is to learn as quickly as possible,” he says

Given testing can be incremental, we don’t have to fail big. Swapping one graphic position for another could barely be considered a failure, and that’s what a testing process is about. It’s incremental, and iterative, and one failure or success doesn’t matter much, so long as it’s all heading in the direction of achieving a business goal.

It’s about turning the dogs into winners, and making the winners even bigger winners.

Feel Vs Experimentation

Web publishing decisions are often based on intuition, historical precedence – “we’ve always done it this way” – or by copying the competition. Graphic designers know about colour psychology, typography and layout. There is plenty of room for conflict.

Douglas Bowden, a graphic designer at Google, left Google because he felt the company relied too much on data-driven decisions, and not enough on the opinions of designers:

Yes, it’s true that a team at Google couldn’t decide between two blues, so they’retesting 41 shades between each blue to see which one performs better. I had a recent debate over whether a border should be 3, 4 or 5 pixels wide, and was asked to prove my case. I can’t operate in an environment like that. I’ve grown tired of debating such minuscule design decisions. There are more exciting design problems in this world to tackle.

That probably doesn’t come as a surprise to any Google watchers. Google is driven by engineers. In Google’s defense, they have such a massive user base that minor changes can have significant impact, so their approach is understandable.

Integrate Design

Putting emotion, and habit, aside is not easy.

However, experimentation doesn’t need to exclude visual designers. Visual design is valuable. It helps visitors identify and remember brands. It can convey professionalism and status. It helps people make positive associations.

But being relevant is also design.

Adopting an experimentation methodology means designers can work on a number of different designs and get to see how the public really does react to their work. Design X converted better than design Y, layout Q works best for form design, buttons A, B and C work better than buttons J, K and L, and so on. It’s a further opportunity to validate creative ideas.

Cultural Shift

Part of getting experimentation right has to do with an organizations culture. Obviously, it’s much easier if everyone is working towards a common goal i.e. “all work, and all decisions made, should serve a business goal, as opposed to serving personal ego”.

All aspects of web publishing can be tested, although asking the right questions about what,to test is important. Some aspects may not make a measurable difference in terms of conversion. A logo, for example. A visual designer could focus on that page element, whilst the conversion process might rely heavily on the layout of the form. Both the conversion expert and the design expert get to win, yet not stamp on each others toes.

One of the great aspects of data-driven decision making is that common, long-held assumptions get challenged, often with surprising results. How long does it take to film a fight scene? The movie industry says 30 days.

Mark Walberg challenged that assumption and did it in three:

Experts go with what they know. And they’ll often insist something needs to take a long time. But when you don’t have tons of resources, you need to ask if there’s a simpler, judo way to get the impact you desire. Sometimes there’s a better way than the “best” way. I thought of this while watching “The Fighter” over the weekend. There’s a making of extra on the DVD where Mark Wahlberg, who starred in and produced the film, talks about how all the fight scenes were filmed with an actual HBO fight crew. He mentions that going this route allowed them to shoot these scenes in a fraction of the time it usually takes

How many aspects of your site are based on assumption? Could those assumptions be masking opportunities or failure?

Winning Experiments

Some experiments, if poorly designed, don’t lead to more business success. If an experiment isn’t focused on improving a business case, then it’s probably just wasted time. That time could have been better spent devising and running better experiments.

In Agile software design methodologies, the question is always asked “how does this change/feature provide value to the customer”. The underlying motive is “how does this change/feature provide value to the business”. This is a good way to prioritize test cases. Those that potentially provide the most value, such as landing page optimization on PPC campaigns, are likely to have a higher priority than, say, features available to forum users.

Further Reading

I hope this article has given you some food for thought and that you’ll consider adopting some experiment-based processes to your mix. Here’s some of the sources used in this article, and further reading:

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SEO Book

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Post-Panda: Data Driven Search Marketing

Now is the best and exciting time to be in marketing. The new data-driven approaches and infrastructure to collect customer data are truly changing the marketing game, and there is incredible opportunity for those who act upon the new insights the data provides” – Mark Jeffrey, Kellog School Of Management

I think Jeffries is right – now is one of the best and exciting times to be in marketing!

It is now cheap and easy to measure marketing performance, so we are better able to spot and seize marketing opportunities. If we collect and analyze the right data, we will make better decisions, and increase the likelihood of success.

As Google makes their system harder to game using brute force tactics, the next generation of search marketing will be tightly integrated with traditional marketing metrics such as customer retention, churn, profitability, and customer lifetime value. If each visitor is going to be more expensive to acquire, then we need to make sure those visitors are worthwhile, and the more we engage visitors post-click, the more relevant our sites will appear to Google.

We’ll look at some important metrics to track and act upon.

But first….

Data-Driven Playing Field

There is another good reason why data-driven thinking should be something every search marketer should know about, even if some search marketers choose to take a different approach.

Google is a data-driven company.

If you want to figure out what Google is going to do next, then you need to think like a Googler.
Googlers think about – and act upon – data.

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Douglas Bowman, a designer at Google, left the company because he felt they placed too much reliance on data over intuition when it came to visual design decisions.

Yes, it’s true that a team at Google couldn’t decide between two blues, so they’re testing 41 shades between each blue to see which one performs better. I had a recent debate over whether a border should be 3, 4 or 5 pixels wide, and was asked to prove my case. I can’t operate in an environment like that. I’ve grown tired of debating such miniscule design decisions. There are more exciting design problems in this world to tackle

Regardless of whether you think acting on data or intuition is the right idea, if you can relate to the data-driven mindset and the company culture that results, you will better understand Google. Searcher satisfaction metrics are writ-large on Google’s radar and they will only get more refined and granular as time goes on.

Update Panda was all about user engagement issues. If a site does not engage users, it is less likely to rank well.

As Jim Boykin notes, Google are interested in the “long click”:

On the most basic level, Google could see how satisfied users were. To paraphrase Tolstoy, happy users were all the same. The best sign of their happiness was the “long click”. this occurred when someone went to a search result, ideally the top one, and did not return. That meant Google has successfully fulfilled the query. But unhappy users were unhappy in their own ways, most telling were the “short clicks” where a user followed a link and immediately returned to try again. “If people type something and then go and change their query, you could tell they aren’t happy,” says (Amit) Patel. “If they go to the next page of results, it’s a sign they’re not happy. You can use those signs that someone’s not happy with what we gave them to go back and study those cases and find places to improve search.

In terms of brand, the more well known you are, the more some of your traffic is going to be pre-qualified. Brand awareness can lower your bounce rate, which leads to better engagement signals.

Any site is going to have some arbitrary brand-related traffic and some generic search traffic. Where a site has good brand-related searches, those searches create positive engagement metrics which lift the whole of the site. The following chart is conceptual, but it drives the point home. As more branded traffic gets folded into the mix, aggregate engagement metrics improve.

If your site and business metrics look good in terms of visitor satisfaction – i.e. people are buying what you offer and/or reading what you have to say, and recommending you to their friends – it’s highly likely your relevancy signals will look positive to Google, too. People aren’t just arriving and clicking back. They are engaging, spending time, talking about you, and returning.

Repeat visits to your site, especially from logged-in Google users with credit cards on file, are yet another signal Google can look at to see that people like, demand and value what you offer.

Post-Panda, SEO is about the behavior of visitors post-click. In order to optimize for visitor satisfaction, we need to measure their behavior post-click and adjust our offering. A model that I’ve found works well in a post-Panda environment is a data-driven approach, often used in PPC. Yes, we still have to do link building and publish relevant pages, but we also have to focus on the behavior of users once they arrive. We collect and analyze behavior data and feed it back into our publication strategy to ensure we’re giving visitors exactly what they want.

What Is Data Driven Marketing?

Data driven marketing is, as the name suggests, the collection and analysis of data to provide insights into marketing strategies.

It’s a way to measure how relevant we are to the visitor, as the more relevant we are, the more positive our engagement metrics will be. A site can constantly be adapted, based on the behavior of previous visitors, in order to be made more even more relevant.

Everyone wins.

The process involves three phases. Setting up a framework to measure and analyze visitor behaviour, testing assumptions using visitor data, then optimizing content, channels and offers to maximize return. This process is used a lot in PPC.

Pre-web, this type of data used to be expensive to collect and analyse. Large companies engaged market researchers to run surveys, focus groups, and go out on the street to gather data.

These days, collecting input from consumers and adapting campaigns is as easy as firing up analytics and creating a process to observe behaviour and modify our approach based on the results. High-value data analysis and marketing can be done on small budgets.

Yet many companies still don’t do it.

And many of those that do aren’t measuring the right data. By capturing and analysing the right data, we put ourselves at a considerable advantage to most of our competitors.

In his book Data Driven Marketing, Jeffrey notes that the lower performing companies in the Fortune 500 were spending 4% less than the average on marketing, and the high performers were investing 20% more than average. Low performers focused on demand generation – sales, coupons, events – whereas high performers spend a lot more on brand and marketing infrastructure. Infrastructure includes the processes and software tools needed to capture and analyse marketing data.

So the more successful companies are spending more on tools and process than lower performing companies.

When it comes to the small/medium sized businesses, we have most of the tools we need readily available. Capturing and analyzing the right data is really about process and asking the right questions.

What Are The Right Questions?

We need a set of metrics that help us measure and optimize for visitor satisfaction.

Jeffrey identifies 15 data-analysis areas for marketers. Some of these metrics relate directly to search marketing, and some do not. However, it’s good to at least be aware of them as these are the metrics traditional marketing managers use, so might serve as inspiration get us thinking about where the cross-overs into search marketing lay. I recommend reading his book to anyone who wants a crash course in data-driven marketing and to better understand where how marketing managers think.

  • Brand awareness
  • Test Drive
  • Churn
  • Customer satisfaction
  • Take rate
  • Profit
  • Net Present Value
  • Internal Rate Of Return
  • Payback
  • Customer Lifetime Value
  • Cost Per Click
  • Transaction Conversion Rate
  • Return On Ad Dollars Spent
  • Bounce Rate
  • Word Of Mouth (Social Media Reach)

I’ll re-define this list and focus on a few metrics we could realistically use that help us optimize sites and offers in terms of visitor engagement and satisfaction. As a bonus, we’ll likely create the right relevancy signature Google is looking for which will help us rank well. Most of these metrics come directly from PPC.

First, we need a…..dashboard! Obviously, a dashboard is a place where you can see how you’re progressing, at a glance, measured over time. There are plenty of third party offerings, or you can roll-your-own, but the important thing is to have one and use it. You need a means to measure where you are, and where you’re going in terms of visitor engagement.

1. Traffic Vs Leads

Traffic is a good metric for display and brand purposes. If a site is making money based on how many people see the site, then they will be tracking traffic.

For everyone else, combining the two can provide valuable insights. If traffic has increased, but the site is generating the same number of leads – or whatever your desired engagement action may be, but I’ll use the term “leads” to mean any desired action – then is that traffic worthwhile? Track how many leads are closed and this will tell you if the traffic is valuable. If the traffic is high, but engagement is low, then visitors are likely clicking back, and this is not a signal Google deems favorable.

This data is also the basis for adjusting and testing the offer and copy. Does engagement increase or decrease after you’ve adjusted the copy and/or the offer?

2. Search Channel Vs Other Channels

Does search traffic result in more leads than, say, social media traffic? Does it result in more leads vs any other channel? If so, then there is justification to increase spending on search marketing vs other channels.

Separate marketing channels out so you can compare and contrast.

3. Channel Growth

Is the SEM channel growing, staying the same, or declining vs other channels?

Set targets and incremental milestones. Create a process to adjust copy and offers and measure the results. The more conversions to desired action, the better your relevancy signal is likely to be, and the more you’ll be rewarded.

You can get quite granular with this metric. If certain pages are generating more leads than others as the direct result of keyword clicks, then you know which keyword areas to grow and exploit in order to grow the performance of the channel as a whole. It can be difficult to isolate if visitors skip from page to page, but it can give you a good idea which entry pages and keywords kick it all off.

4. Paid Vs Organic

If a search campaign is running both PPC and SEO, then split these two sources out. Perhaps SEO produces more leads. In which case, this will justify creating more blog posts, articles, link strategies, and so on.

If PPC produces more leads, then the money may be better spent on PPC traffic, optimizing offers and landing pages, and running A/B tests. Of course, the information gleaned here can be fed into your organic strategies. If the content works well in PPC, it is likely to work well in SEO, at least in terms of engagement.

5. Call To Action

How do you know if a call to action is working? Could the call to action be worded differently? Which version of the call to action works best? Which position does it work best? Does the color of the link make a difference?

This type of testing is common in PPC, but less so in SEO. If SEO pages are optimized in this manner, then we increase the level of engagement and reduce the click-back.

6. Returning Visitor

If all your visitors are new and never return, then your broader relevance signals aren’t likely to be great.

This doesn’t mean all sites must have a high number of return visitors in order to deemed relevant – one-off sales sites would be unlikely to have return visitors, yet a blog would – however, if your site is in a class of sites where every other site listed is receiving return visits, then your site is likely to suffer by comparison.

Measure the number of return visitors vs new visitors. Think about ways you can keep visitors coming back, especially if you suspect that your competitors have high return visitor rates.

7. Cost Per Click/Transaction Conversion Rate/Return On Ad Dollars Spent

PPC marketers are familiar with these metrics. We pay per click (CPC) and hope the visitor converts to desired action. We get a better idea of the effectiveness of keyword marketing when we combine this metric with transaction conversion rate (TCR) and return on ad dollars spent (ROA). TCR = transaction conversion rate; the percentage of customers who purchase after clicking through to your website. ROA = return on ad dollars spent.

These are good metrics for SEOs to get their heads around, too, especially when justifying SEO spends relative to other channels. For cost per click, use the going rate on Adwords and assign it to the organic keyword if you want to demonstrate value. If you’re getting visitors in at a lot lower price per click the SEO channel looks great. The cost-per-click in SEO is also the total cost of the SEO campaign divided by clicks over time.

8. Bounce Rate

Widely speculated to be an important metric post-Panda. Obviously, we want to get this rate down, Panda or not.

If you’re seeing good rankings but high bounce rates for pages it’s because the page content isn’t relevant enough. It might be relevant in terms of content as far as the algorithm sees it, but not relevant in terms of visitor intent. Such a page may drift down the rankings over time as a result, and it certainly doesn’t do other areas of your business any good

9. Word Of Mouth (Social Media Reach/Brand)

Are other people talking about you? Do they repeat your brand name? Do they do so often? If you can convince enough people to search for you based on your name, then you’ll “own” that word. Google must return your site, else they’ll be seen as lacking.

Measuring word-of-mouth used to be difficult but it’s become a lot easier, thanks to social media and the various information mining tools available. Aaron has written a lot on the impact of brand in SEO, so if this area is new to you, I’d recommend reading back through The Rise Of Brand Over Time, Big Brands and Potential Brand Signals For Panda.

10. Profit

It’s all about the bottom line.

If search marketers can demonstrate they add value to the bottom line, then they are much more likely to be retained and have budget increased. This isn’t directly related to Panda optimization, other than in the broad sense that the more profitable the business, the more likely they are keeping visitors satisfied.

Profit = revenue – cost. Does the search marketing campaign bring in more revenue that it costs to run? How will you measure and demonstrate this? Is the search marketing campaign focused on the most profitable products, or the least? Do you know which products and services are the most profitable to the business? What value does your client place on a visitor?

There is no one way of tracking this. It’s a case of being aware of the metric, then devising techniques to track it and add it to the dashboard.

11. Customer Lifetime Value

Some customers are more important than others. Some customers convert, buy the least profitable service or product, and we never hear from them again. Some buy the most profitable service or product, and return again and again.

Is the search campaign delivering more of the former, or the latter? Calculating this value can be difficult, and relies on internal systems within the company that the search marketer may not have access to, but if the company already has this information, then it can help validate the cost of search marketing campaigns and to focus campaigns on the keyword areas which offer the most return.

Some of these metrics don’t specifically relate to ranking, they’re about marketing value, but perhaps an illustration of how some of the traditional marketing metrics and those of search marketers are starting to overlap. The metrics I’ve outlined are just some of the many metrics we could use and I’d be interested to hear what other metrics you’re using, and how you’re using them.

Optimizing For Visitor Experience

If you test these metrics, then analyse and optimize your content and offers based on your findings, not only will this help the bottom line, but your signature on Google, in terms of visitor relevance, is likely to look positive because of what the visitor does post-click.

When we get this right, people are engaging. They are clicking on the link, they’re staying rather than clicking back, they’re clicking on a link on the page, they’re reading other pages, they’re interacting with our forms, they’re book-marking pages or telling others about our sites on social media. These are all engagement signals, and increased engagement tends to indicate greater relevance.

This is diving deeper than a traditional SEO-led marketing approach, which until quite recently worked, even if you only operated in the search channel and put SEO at the top of the funnel. It’s not just about the new user and the first visit, it’s also about the returning visitor and their level of engagement over time. The search visitor has a value way beyond that first click and browse.

Data-driven content and offer optimization is where SEO is going.

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