Meaningful SEO Metrics – #SESSF

August 16, 2011 by  
Filed under Online Marketing, SEO, Web Analytics

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SEO Metrics Panel SES San Francisco 2011The only session I’m liveblogging day one of SES San Francisco conference is this one, “Meaningful SEO Metrics: Going Beyond the Numbers” so the pressure is on the awesome panel including: Todd Friesen, Ray “Catfish” Comstock, Rob Garner and moderation duties handled by Richard Zwicky.

First up is Rob Garner, VP Strategy at iCrossing and a VP at SEMPO. Rob started things off with a description of the challenges that most often occur with measuring the search channel.

90% of search channel bugets go to paid media, but paid media supplies 20% of returns. Only 10% of budgets go to SEO but a huge percentage of search marketing performance can be attributed to SEO.

Why is this? Paid search is easier to measure. But… SEO can be made easier to measure in aggregate and at the keyword level once a balanced program is implemented. The biggest opportunities in search are with SEO.

Challenges on the client side regarding measuring SEO performance:

  • Disconnect between legacy systems in tracking performance
  • Using last click attribution
  • Large companies measure value as “what have you done for me lately” natural search benefits tend to be longer term
  • Not maintaining search performance history going back years
  • Bad analytics and tracking
  • Educating those holding the budgets for natural search

A longer term view of natural search is needed to understand the value. Natural traffic is earned but eventually owned. Look at maintenance costs of SEO as a realistic expense, especially in comparison to the contribution to revenue.

4 Key measurements needed for meaningful SEO metrics:

  1. Value of searchequity for the site being optimized
  2. Media value of natural search traffic
  3. Value o various action across the site (individually and in aggregate)
  4. Value of the stress and time costs on your organization. The cost savings of doing it now, vs. doing it later (retro-fit)

Building a Business Case – Key Questions

  1. How much is invested in search
  2. How much is a conversion worth? How much will it change with SEO?
  3. How do we measure lift in natural search metrics
  4. How much opportunity may be lost without a SEO plan?

Calculating Advertising Value Equivalent for SEO:

  • Find out the anticipate traffic lost or gained in natural search
  • Determine the average CPC in a themed area of one of your campaigns
  • Multiply the average CPC times the amount of SEO traffic to quantify its media value. For example: 100k clicks times an average CPC of $2.63 is valued at $253k. In a year, that value is over $3 million.

Case Study:  A banking site re-launched with renamed URLs and no redirection plan. There was a spike in 404 errors and $1.5m in actual revenue per month lost.

Marketers must place a monetary value on actions to help SEO quantify results. Place a value on actions and also on lifetime value. When forecasting potential lift from SEO, be very conservative with traffic estimates.

Be sure to measure Year over Year trends, not just month to month to create context for growth and overall perfornance.

Next is Todd Friesen, Director of SEO for Performics who talked about incorporating SEM and SEO reporting to draw attention to the impact of SEO. “SEO hasn’t been getting it’s due”

Benefits of a combined SEO and PPC strategy:

  • Visibility in both paid and natural decreases the frequency that consumers select a competitor
  • Great opportunity to increase overall revenue
  • Both can result in a significant lift in brand visibility

Managing both tactics holistically yields great results than using any one tactic. A big problem is that measuring in silos doesn’t give a complete picture.

Strategies for effective PPC and SEO:

  • Max ROI by adjusting bid strategy based on SEO ranking data
  • Keyword Gap Analysis – Identify strong performing keywords missing from your campaigns by comparing your SEO and PPC keyword lists
  • Increased Efficiency – Share landing page and ad creative across disciplines. Ad text used as meta description tags.
  • Creative Sharing – Share top performing ad creative with SEO for CTR optimization
  • Clickshare / SERP Domination – Rolled up reporting identifying tru combined clickshare numbers

Testing framework for SEO and PPC vs. SEO alone: Identify top ranking organic keywords, select keywords for test and control groups, define hypothesis and success metrics, apply the test, evaluate the results and iterate.

SEO and SEM do not exist in silos. It’s only in the past few years that marketers are actually figuring out how they can work together – looking at data and approaching it holistically.

Last up is Catfish, Director of SEO at Business Online who focused on key metrics and reporting.

Key Metrics: How to tell if you’re winning or losing. Three phased approach. Performance, opportunity and prioritization

Performance Reporting:
Search Rankings – It used to be that when you ranked #1 on Google, you ranked #1 on Google but now rankings can vary according to localization and personalization. Search rankings can be useful for month over month comparisons, but otherwise are not the best indicator of success.

Tips on Effective SEO Performance Measurement:

  • Segment keyword campaigns according to levels of specificity. Example: Campaign (Dog), Group (Dog Food), Keywords (Buy Dog Food).
  • Distinguish brand versus non-brand performance
  • Look at long tail performance.

Take your keywords and break them into groups, segment into brand vs. non-brand terms plus long tail keyword performance year over year.

SEO Intelligence is a service that leverages Adobe Insight to look at SEO data. It tracks at the visitor level and supports cross channel attribution (online and offline). Also supports predictive modeling. Ray is very enthusiastic about SEO Intelligence!

There were a few audience questions but I’ve used that time to finish off this post so I can publish it within a reasonable time.

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5 Social Media ROI & Measurement Books to Grow Your Social Business

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Books Social Media MeasurementOne of the most compelling challenges for companies entering the world of social business is measurement. The ability to attribute cause and effect directly can be elusive when it comes to measuring business outcomes like increased sales, improved customer retention and lowered support costs. But that’s only because this is new territory.  Business participation with social media on the web at large and internally has absolutely made measurable progress for numerous companies and organizations. The trick is to learn how, create a model that works for you and to sell it internally for testing, implementation and adoption.

One way to facilitate learning about Social Media ROI, Measurement and Analytics is through books from subject matter experts. Here are 5 that I’ve found useful and hopefully, you will too.

Social Media ROI: Managing and Measuring Social Media Efforts in Your Organization
by Olivier Blanchard

There are many other books on social media strategy, but in your pursuit of social ROI enlightenment, I’d start with this one (it’s also very new) because it covers social program development and management as well as measurement.  Olivier’s presentation on the Basics of Social Media ROI from a few years ago completely opened the eyes for many (including myself) on basic ways to approach the impact of social media on tangible business goals. It’s damn funny too.

Social Media Metrics: How to Measure and Optimize Your Marketing Investment
by Jim Sterne

This may be one of the first books dedicated to socia media metrics and Analytics guru Jim Sterne does a great job of setting ground rules. This book isn’t about justifying social media at large or a collection of tactics. It takes you from goal setting to audience, influence, sentiment, action, conversation and business outcomes. Once you have all that, there’s advice on communicating your newfound social media measurement wisdom to the organization.

Measure What Matters: Online Tools For Understanding Customers, Social Media, Engagement, and Key Relationships
by Kattie Delahaye Paine

Katie Paine is the master of Public Relations and Social Media measurement and her new book is a great complement to our mix because it comes from a perspective of measuring and affecting influence, engagement and relationships – not just sales and revenue. Katie outlines how to get started with a measurement program, how to choose the right tools and she answers measurement “how” questions related to marketing and public relations, events, thought leadership, community, internal staff and crisis situations. This is a measurement bible for the social media and public relations savvy professionals of the world.
(Read our Public Relations Measurement interview with Katie)

Web Analytics 2.0: The Art of Online Accountability and Science of Customer Centricity
by Avinash Kaushkik

If you’re even remotely familiar with web analytics, then you know the blog Occam’s Razor by Google’s Analytics Evangelist, Avinash Kaushik. In his enthusiastic and entertaining style, Avinash explains the next generation framework of web analytics including social media measurement and includes specific guidance on hiring analytics resources, practical advice on the practice of  gaining insight from clickstream data and analysis, plus how to help managers become more data-driven in their decision making.
(Watch our video interview with Avinash at SES Hong Kong)

Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites
By Matthew A. Russell

After you’ve read the books above and you’ve either tasked an internal analytics guru or hired someone for your social media measurement and analytics, then they really need to dig into this book. When business, marketing or PR managers ask question like, “How can we create our own tools to mine our prospects social web activity?” this is a great guidebook into the mechanics of making that happen. Matthew covers “data hacking” for Twitter, Blogs, Facebook, Google Buzz and LinkedIn plus how to visualize that data in a meaningful way.

While this is no comprehensive list of social media ROI, measurement and analytics books, it is a great collection to start with.  What books social media measurement books would you recommend?

(For the first time in 7 years, I’ve added Amazon affiliate links to these book URLs. Since we don’t sell ads here, I’m hoping you can appreciate  that effort).

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10 Questions for Social Media Measurement Success

social media measurementIn order for companies to realize the maximum benefit and impact from social media marketing, the pre requisite for goal setting must be a certain level of understanding about the nature of online communities, social media sharing web sites and applications.  Unrealistic expectations based on a lack of knowledge about the social web is far too expensive to ignore.

At Search Marketing conferences, you’ll hear a lot about driving website traffic and links through social media linkbait – a SEO tactic that is distinctly different than what goes into building customer relationships. Companies like Proctor & Gamble are paying for engagement, not eyeballs.

Companies that want to take full advantage of better customer engagement, online word of mouth and influence on sales should ask themselves a few key measurement and related questions while developing a social media strategy:

  1. What goals do you hope to achieve from a social media marketing effort? What does success REALLY look like short and long term? This is according to the segments or divisions of business affected, not just the organization as a whole. Customer service success is obviously very different than Marketing or Public Relations.
  2. Are web and social media synced? How will current web analytics and other digital performance reporting interact with social media marketing analysis?
  3. What measures of success (KPIs and Outcomes) will be used? How are you defining ROI?
  4. Is there a strategic plan for coordinating and measuring social media efforts across the organization? Will these efforts work synergistically? In silos?
  5. What are current measures? Is the business conducting a formal effort at monitoring social channels using a social media monitoring/analysis software application? (Ex: Alterian SM2, ScoutLabs, Sysomos, Trackur, Vocus (TopRank Client), SocialRadar, Radian6) Are different business units using different monitoring tools? Are analysis staff allocated to making sense of the data and reporting?
  6. Where to start? Is there a particular business unit, division or product that can serve as a test case?
  7. What’s the current tactical mix? Assess current social media activities: How long has the company participated with social media sites and which? Blogging, Facebook, MySpace, LinkedIn, Twitter, Flickr, YouTube, Wikis, Delicious, Digg, StumbleUpon, etc. Identify your benchmark measurements with relevant channels.
  8. Is a dashboard and social media marketing management tool used for content promotion?
  9. Moving forward, what will it take to transition from fragmented efforts to something more coordinated? Which “hearts and minds” do you need to win over for support to make it happen?
  10. Is there an internal social media council or group tasked with assessing social media strategy and how will their role affect defining goals and ongoing performance reporting?

Every company, division, product/service and their customers are unique. The questions above can provide valuable insight into a company’s state of social media marketing readiness as well as provoking new thoughts and direction. The more informed companies are about planning for the social web, the more successful they will be.

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6 Ways to Dive In to Analytics & User Experience

September 29, 2010 by  
Filed under Online Marketing, Web Analytics

This post is one of a series of liveblogs from the 2010 MIMA Summit.

Web Analytics is an excellent way to ensure your marketing efforts are not in vain. However, looking at Analytics without understanding user behavior may leave you treading water instead of creating a wake your competitors will fear.Web Analytics

One way to take your methods of measurement to the next level is to combine Analytics with User Experience (UX) information. What you stand to gain can be great whether you dip a toe or cannon ball into blended analytic waters.

To make sure you don’t sink, first understand that Analytics will tell you what’s happening on the site. User Experience Research then helps you understand why it’s happening by gaining insight into the behaviors and motivation of visitors.

When you combine both, you can start to understand the What and the Why of what’s happening on your website. This also allows any potential problems to float to the top more quickly, allowing you to see the problem you need to solve and what changes might do just that.

The following case study illustrates what you can find when you combine the power of Analytics and user behavior:

An insurance quoting website, which had a 14 page quote and purchase process was going through a website redesign and decided it was the perfect time to double check their form process.

The goal was to identify where in the funnel visitors were getting stuck and abandoning the process.

After understanding user experience and their reactions to what you are testing, the data should be compared to Analytics. Does Analytics show visitor ‘drop-off’ points in similar places as what was identified as confusing/irritating by the users?

To understand drop-off points and not spend time in lower-priority places, be sure to identify logical places for drop-off. In this example a make-sense drop off would be after the quote is delivered because you can expect that some visitors won’t like the quote they received and abandon to either get a different quote or purchase elsewhere.

Where you want to spend time is identifying the unexpected drop-offs. One such drop-off point for the health insurance quote form was the request for a social security number. Almost all users are cautious when giving such information online, but the problem in this particular case was that the information was asked for too early in the process before the person is invested.

As such, they identified an item to test. After placing the request for the social security number further into the funnel where the user was more invested and felt like it was OK to give their personal information, the abandonment rate decreased.

The next drop-off point was the question of where they attended college, which some – via the user experience testing – found offensive and/or didn’t understand how it was relevant to an insurance quote. The Analytics confirmed this and showed a higher than normal drop-off rate at the point that question was asked in the funnel.  Ask yourself, why is this question part of the form? Is it necessary? If not, remove it and improve the percent of visitors who get further in the funnel and closer to a sale.

Start getting more out of your website by diving deeper into the following 6 areas using both Analytics and User Experience Data:

1. Landing Page Optimization
Analytics: Bounce Rate, Conversion Rate
UX: Why people convert.

2. Site Navigation
Analytics: Top Content
UX: How they get there

3. Form Completion
Analytics: Abandonment, Page reloads
UX: Specific Objections

4. Content
5. Analytics: Time Spent on page
UX: Is it engaging?

5. Testing
Analytics: A/B Testing
UX: What to Test

6. Terminology
Analytics: Search Logs
UX: How people use language – what is your target marking using to search for you

In the case that you need to dip your toes, go old-school and simply sit behind someone and watch them navigate your website. Where do they go first, second, third, what do they avoid? Ask them why. Some data is better than no data.

Thank you to Fred Beecher and Andrew Janis of Evantage Consulting for presenting the above case study and tips on UX and Analytics during the 2010 MIMA Summit.

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Avinash Kaushik on Storytelling & Web Analytics

September 14, 2010 by  
Filed under Online Marketing, Search Engine Strategies, Web Analytics

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avinash kaushikThe opening keynote presentation at SES Hong Kong featured none other than Avinash Kaushik, co-Founder of Market Motive Inc and the Analytics Evangelist for Google.

In this video interview, Avinash talks about the value of communicating analytics information in more meaningful ways. He gives examples of metaphors he’s used to present important analytics information that helps others better understand the meaning and implications of the data. There are lessons here for companies that report tabular data with no insight and little creativity in communicating insight.

Click here to view the embedded video.

What creative ways have you found to communicate web analytics insights? Have you had nightmare experiences with web analytics reports?

Check out Avinash’s “must-read” web analytics blog, Occam’s Razor, here.

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Is It The SEO Metrics Or The Connections Between?

Meaningful SEO Metrics at SES San Francisco Ultimately, to measure Search Engine Optimization (SEO) success, you aren’t necessarily looking at individual metrics – you are looking for a connection between the metrics – and the resulting affect on revenue.

If my lead seems to negate the name validity of the SES San Francisco session, ‘Meaningful SEO Metrics,’  it is completely unintentional.

Moderated by John Marshall, CTO of Market Motive and SES Advisory Board Member, this excellent session featured on its panel:

  • Richard Zwicky, Founder & CEO, Enquisite
  • Ray “Catfish” Comstock, Director of SEO, BusinessOnLine
  • Jon Glick, VP of SEO and GM European Web Properties,

“Infinitely measureable means adjustable,” opens Zwicky.  “And online marketing is completely measureable.”

A Key Performance Indicator (KPI) Zwicky recommends companies and marketers look at is Share of Voice, or in other words, how much traffic are you receiving for a keyword or phrase when compared to the balance of the marketplace?

Online tools, from Google Trends to Tweetscan, can measure the amount of traffic or conversation generated by competing websites or in social platforms to give you an idea of just how much voice is out there. It’s not perfect, but it’s measureable.

Another KPI from Zwicky is attribution across channels.  For example, plot out the sales your company achieves on a local or nationwide map.  Next map out visits from social media, local media buys – or any other metric you would like to compare against.  You now have a quick and dirty map that can be used to compare your metrics and help measure the effectiveness of your tactics.

Zwicky’s map segues nicely into Comstock’s keyword metrics, specifically branded vs. non-branded traffic, long-tail keyword traffic and personalized vs. local rankings.

Branded keywords, traffic coming to your site via queries containing your brand name, are oftentimes more an effect of outreach programs while non-branded are an effect of SEO.  Long-tail keyword traffic, the iceberg below the water, measures all the variations of popular keyword phrases driving traffic to your site. Finally, personalized vs. localized rankings are everything that will appear above traditional search results – at times wreaking havoc for those used to a certain ranking position.

Combine the insight of Zwicky and Comstock – for instance – analyze branded traffic in  markets where media buys are heavier, and you have an indication of the effectiveness of your ad campaigns in driving traffic.  Analyze corresponding revenue and you have an indicator of the effectiveness of your ad campaigns towards sales.

Glick closes the session by continuing to urge audience members to see how data fits together, and to implement the types of tests that will show these connections.

‘Pseudo A/B testing,’ the process of adding new features to subsets of pages, can help illustrate the connections between minor and major website updates and corresponding changes to the bottom-line.  Pseudo A/B testing offers infinite possibilities for analyzing the types of changes that can be made to compel bottom-line results when implemented sitewide.

The path towards online success is driven by data of a different stripe daily.

What metrics, or connections, have you found beneficial to look at?

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Is It The SEO Metrics Or The Connections Between? |

Website Analytics vs. The Myth of 100% Accuracy

Deep Dive Into Website Analytics At SES San FranciscoLet’s get this out of the way.  100% accuracy does not exist in website analytics.  Repeat. 100% accuracy does not exist in analytics.

What does exist in analytics is data – lots of it – and with this comes fear.

Fear of looking at the wrong data.  Fear of where to start.  Fear of analytics failure.

This fear will only dissipate with knowledge.  Knowing that analytics will never be perfect is a critical first step and a cornerstone shared during the session ‘Deep Dive Into Analytics’ at SES San Francisco.

Bryan Eisenberg, SES Advisory Board and NY Times bestselling author, moderated this session which included on its panel:

  • Tami Dalley, Director, User Experience Optimization, ROI Labs
  • Marty Weintraub, President, aimClear
  • Matthew Bailey, SES Advisory Board & President, Site Logic Marketing

The beauty of an analytics session at SES is that those on the panel may sometimes be analysts or they may sometimes be statisticians, but they are always marketers.  And a good marketing analyst knows that it’s the facts that tell and the stories that sell.

As such, Bailey shaped his presentation around four key points that make up the bulk head of the website analytics story:

  1. Intent
    Every visitor that lands on your website is there for a reason.  Bailey offers the example of a jewelry store pulling traffic for ‘watch’ based keywords.  Within this segment, some will be looking to ‘buy a rolex’ while some will be looking to ‘fix a watch + san francisco.’  Based on the keywords this segment used to find your site, did content match intent?
  2. Expectancy
    Similar to intent, but expanded to include referring sites ranging from forums to blogs.  Did the source that referred the segment, say a forum about watch repair stores in San Francisco, shape user segment expectations accurately in regards to what they found on your site?
  3. Reaction
    What ultimately happened when the segment of users arrived on your site?  Did they bounce immediately? Convert?  Did they do what you intended them to do?
  4. Behavior
    Whether the user bounced, exited or converted, what behavioral clues did they drop along the way? Did they bounce after a mere ten seconds? Exit after visiting multiple pages?  Convert directly from where they landed or within just one step?

Remove these items from a numbered list, and add context, and this becomes an actionable story:

Users arriving at my site using San Francisco watch repair related keywords, or coming from local websites geared towards watch repair services, are bouncing at a rate of 85% and converting at a rate of 4%.  However, those that land on my Rolex repair services page from this same segment bounce at a rate of 60% and convert at a rate of 10%.  If I optimize my Rolex repair page for ‘rolex repair + san francisco’, I may capture more conversions.

Of course, the answer is never quite so simple.  Dalley and Weintraub illustrate this as they share detailed real world case studies and conversion reports, respectively.

Dalley’s case studies detail how the slightest change, from a page’s design to a customer’s location, can drastically shape results.  The key to making an actionable change is to start with an educated hypothesis before backing it up with the right data for proof points.

And this means overcoming a fear of data and digging in, as repeated by Bailey.

Since Weintraub is sorely misrepresented in this post, primarily because nearly any written word would be a severe injustice to the energy level he brings to his presentation, below find potential conversion reports or data ‘dig-in points.’  These are reports that you can pull from your analytics to make a decision from today.  The list below was both leveraged from and inspired by a list of deeply ‘unsexy’ (Weintraub’s words, not mine) possible conversion reports shared during this session:

  1. Conversion by time of day
  2. Conversions by rural Pennsylvania city
  3. Conversions by mobile device
  4. Conversions by web browser
  5. Conversions by keywords containing the keyword ‘green dress’

Please add your own unsexy, or even sexy, conversion reports or analytics stories via a comment below.

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Website Analytics vs. The Myth of 100% Accuracy |