Infopresse Marketing Conference Recap

This past Tuesday I was at the Infopresse Marketing Conference which had four speaker sessions looking at various topics in the analytics, SEO and SEM spaces. This is a recap of the most important points that were covered during the day.

Paul Bernier’s Advanced Google Analytics Takeaways

Paul Bernier’s presentation was focused on providing insight on how Google Analytics (GA) can be effective for one’s business. Although most of what he spoke about was extremely interesting, there are three main points I would like to discuss from his presentation that I thought were the most insightful. The first point was measuring video content on GA. This is interesting because it not only provides data for how many people view the video but shows where the people came from, where did they go after the video and at what point during the video they stopped watching.

Paul had done work for a car client and developed weekly webisodes . At first glance, this seemed like a great idea for generating a community around the web series, getting some video content ranking in the SERPs and implementing a more interactive call to action. However, based on his post mortem, Paul would be reluctant in advising clients to produce video content on a regular basis because it is extremely expensive to create and does not add any additional value that a well-written article cannot offer.

The second point of interest in Paul’s presentation is the distinction between traffic sources and conversion sources. To illustrate this, let’s take a PPC campaign and assume that 10 visits are generated at noon without any converisons. However, in the evening, one of the visitors that came to the site at noon via PPC comes back via a branded search in Google and converts. At first glance, analytics will tell you that the PPC campaign is not converting and should be stopped but what it doesn’t explain is the conversion it created at a later date.

The final point that was discussed during the questioning period of Paul’s presentation is the advantages and disadvantages of using Omniture versus GA. The consensus was Omniture requires a large investment up front from the client or website for a less than equal increase in value. To put it in perspective, it requires a year-round programmer dedicated to pulling the required data from Omniture as well as a large licensing fee depending on your site’s traffic numbers.

Nectarios Economakis’ Impact of Traditional Media on Online Media Takeaways

Nectarios shared three really interesting case studies that were conducted regarding the impact that traditional advertising had on online media and vice versa. The first case study was conducted by Concordia University and looked at what the effects of television advertising had on websites. After the television campaign was completed, there was an increase in branded search queries for 9 weeks that followed the ad campaign with the number of searchers diminishing week by week.

The second case study discusses the impact PPC has on offline sales in Pier 1 Imports stores across Canada. The study took 50% of the stores’ locations (test group) and ran a PPC campaign in those regions and left the remaining 50% of stores untouched (control group). The results showed an average increase in retail sales by 2% with struggling stores seeing an increase in sales as well.

The third case study that Nectarios presented was the effect banner ads for West Jet had on organic search. Over and above the click through traffic that occurred from having banner ads on high traffic websites, the banner ads resulted in a 22% increase in organic brand searches. One of the reasons why the traditional media resulted in branded organic traffic is because people consume traditional media with their mobile phone or computer nearby. This simplifies the process of going online to continue their engagement with the brand after they are exposed to a traditional ad. Although it is clear that offline and online media are connected, the real prize lies in the conversions that occur online because of traditional advertising. Unfortunately, this area is still very difficult to measure and is hard to justify in its current state.

Gord Hotchkiss’ Understanding Intent and Attitudes of Search Engine Users Takeaways

This was definitely the biggest surprise of the Infopresse Marketing Conference. Gord examined the intent, habits and expectations people have when they use search engines for information sources. Since the beginning, Google has provided user with a tool for aggregating all the information on the web and presenting the most relevant sources to the user. Although this goal needed to be solved back when search engines didn’t exist, it is not entirely true today.

Websites like Expedia, Amazon and Netflix are all sites that have changed the attitudes and expectations people have when searching for vacations, books and movies respectively. For example, Google requires the user to piece together travel information found in multiple Google queries while Expedia does it entirely for the user. Once you purchase one book or watch one movie on Amazon or Netflix, your personal preferences are recorded to better serve you in the future. Although Google is going along this route with personalization, planning an entire trip on Google is still a headache.

Understanding user intent and their habits will become an important part of SEO and has to do with more qualitative measurement. For example, if someone is looking to buy a car, they may look at reviews, what their friends posted on Facebook or Tweeted, company press releases and so on. They aren’t just going to check out BMW’s website and buy a car. It will take a little more research. It is not enough to have rankings strictly on the keywords that bring the most revenue but rather keywords that cover an entire vertical.

What if BMW had monthly press releases, was active on Twitter and Facebook , and constantly got reviews by large and medium sized car review blogs? They would have a lot more web real estate covered. The person searching for a new car might see one of his friends tweeted about unique feature found on the new BMW, or read a review by a source they trust. This will embed the BMW brand even deeper in the customer’s brain. This boils down to understanding the search habits of your customer and providing content to match those needs.

Avinash Kaushik on Analytics & Failing Faster

While we were at The Art of Marketing show in Montreal last week, we got a chance to catch up with Avinash Kaushi., the Analytics Evangelist at Google, and author two books: Web Analytics an Hour a Day and Web Analytics 2.0. Avinash gave a great presentation (in my opinion, the best of the day) on how to suck less, but he also took a few minutes to chat with us on camera.

First, Avinash discusses with us the opportunity that marketers have through web analytics. Specifically, he talks about how analytics let us fail faster and then adapt our online strategies to actual market trends more quickly.

Then, Avinash goes on to talk about the what mistakes companies make most often online. Here, he focuses on how so many brands take their offline “shout marketing” methods, and try to implement it online.

How to Suck Less: Avinash Kaushik @ The Art of Marketing

This post is my take on a recent presentation I attended.

I had the opportunity yesterday to listen to Analytics guru Avinash Kaushik speak at the Art of Marketing Conference here in Montreal.  Of all of the speakers in the lineup, I had been looking forward to hearing Avanish most because I thought that I may learn something practical about marketing – in this case using the Google Analytics tool – that I didn’t already know.

As it turns out, I didn’t come away with any new Analytics trick, but I did come away with a strengthened belief in the power of Analytics as the backbone of a successful online business strategy.  I was already a believer in this, but watching Avinash speak about Analytics so passionately made me not only a bigger believer, but also made me more aware of my responsibility as an online marketing strategist and Accounts Manager to ensure that my clients also understand the power of Analytics data.

Avinash’s main point in his presentation was that Analytics are about understanding your customers and website visitors, and using this understanding to provide them with exactly the kind of content they are looking for.  Or in simpler terms, as he put it, to “not suck”.

As an example of what sucking means to Avinash, he demonstrated search engine results (from Bing) for the keyword “fuel efficient suv 2010”, and proceeded to show that each of the top results, which were all of top vehicle brands, led to a page which had nothing to do with SVU’s at all.  It’s hard to argue against the suckiness of that.

Avinash also highlighted the fact that many big-brand businesses still use the online marketing channel to shout at consumers, and showed the example of the Telus Twitter channel which is chock full of promotional tweets.  As a contrast, he showed the Red Bull Facebook page which is engaging, entertaining, and creates a community around Red Bull-sponsored athletes.

The solution to sucking less, he says, is to use Analytics to understand your customers and then engage them by thinking differently.  He says to slash, burn and re-imagine everything you know about marketing.

Getting into the nitty gritty of Analytics evangelizing, he took some time to show the audience how to dig a little deeper into the data to get to the really insightful stuff.  Although I didn’t learn anything new (I already know it’s important to look at bounce rate, as I’m sure most Analytics users do), I really liked his emphasis on what he called “segment or die”.  What he meant was, go much much deeper than bounce rate, or overall traffic volume, or any of the basic data that is at the surface.  As he said it, data in aggregate is crap, so segment.

I love this because I go to great lengths to dig as deep as possible into the Analytics data of my clients’ websites to present them the most insightful information possible that is relevant to our goals.  But no matter how deep I dig, I always know that it is possible to go even deeper, and to understand even more about the customers and users of the website.  To me, this is the wonder of Analytics.

Translating the vast amount of data into something that clients can understand, value and use remains an ever-present challenge to me and, I suspect, to every other online marketer.  Avinash provided an example of how he uses his Analytics data, whereby he applies a pre-determined monetary value to each non-ecommerce website conversion (i.e. “about page” visits) and is then able to translate data into an easily-understandable value (i.e. $26,000) for the non-“marketing dork” types.

What I took away from Avinash’s presentation is that the power of Analytics continues to be a vastly underestimate and underused tool, and that as internet marketers it is our responsibility to not only unleash it’s potential, but to help our clients to also see the value of it as part of a successful business strategy in the world of new marketing.

Live Blogging SES Toronto 2009: Campaign Performance Tracking: Basic Tips

Moderator: Richard Zwicky, Founder & CEO, Enquisite

Speakers:
Alan Knecht, Founder & President, K’nechtology Inc.
Julie Batten, eMarketing Manager, Klick Communications
Janice Hatch, Account Manager, Google Canada

Overview from the SES Day 2 Agenda:

Yes, you can do that! Many digital marketers are unaware of just how easy it is to install tracking solutions to help track return on investment right down to the keyword or ad level. Panelists will show you precisely what to do to get set up, and explore different techniques for measuring and adjusting campaigns based on key insights. Topics include Google AdWords Conversion Tracker, Google Analytics, and third party tools that can provide advanced analytics and even insight into “invalid” clicks. This panel is aimed at a beginner to intermediate level marketer (*not* advanced) and will cover both technical and strategy issues.

First speaker: J. Batten

[Very brief, superficial look at using Google Analytics, AdWords conversion tracking and using them to meet key performance indicators (KPIs). Next…]

Second speaker: J. Hatch

Campaign performance tracking using Google Analytics.

Use Analytics to:

  • Focus budget on campaigns delivering ROI
  • Optimizing campaigns that don’t deliver results
  • Optimize landing pages

Use Analytics to measure a number of KPIs (it’s not always just revenue you want to look at).

Gave case study of using Analytics for GoogleStore.com, which sells all of Google’s branded merchandise. Using Analytics to find out what countries are bringing best per visit value, most revenue. Can then drill down to see, for example, which particular US states delivered most revenue. (Forty percent of US revenue came from California.)

Analytics provides direction on what campaigns/segments to focus on first.

Use Analytics to find out the most profitable keywords. Expand, build out those terms that are working well.

Landing page optimization. Bounce rate is a great way to measure impact and performance of landing pages. Obviously, you don’t want a high bounce rate (e.g., people leaving your site after just one or two clicks). Look at pages with low bounce rates and try to distill what’s working there and apply that to other pages; improve pages with high bounce rates. Comparing paid vs. all traffic: if, say, paid traffic for a particular page has a higher bounce rate than all traffic, perhaps the ad creative is not as relevant and should be revised. Beyond a certain bounce rate, you can also just say that a page is not effective… compare it to overall numbers (like of a certain category of your site).

More info at youtube.com/googleanalyitcs and Analytics blog.

Third speaker: A. Knecht

Start out by asking: what is a click worth? Are all clicks to your site worth the same? Depends on who’s clicking, where they are clicking from, immediate / long term outcome (segmentation)

Segmentation. Must break down campaigns into component parts for analysis: geographic, demographic, etc. Without segmentation: you can only know how the total campaign is doing; can’t isolate successes or poor performers; missing details and all valuable data in your web analytics; only looking at the big picture instead of the important details.

Analyze segmentation by knowing KPIs; identify specific segments; configure your analytics tool accordingly (filters to include only specific traffic); compare same KPI vs. different segments; don’t pay the same for lower performing segments.

Also, can tend to have high conversion rate for certain landing pages, compared to rest of site. This may rest with the fact that the landing page has limited navigation, and there’s only one action to take on the page (like a purchase). So a high bounce rate here compared to the rest of the site might not necessarily be bad. Would need to look and see how that page is converting compared to the rest; how much sales it’s producing.

SES Toronto : Web Analytics Track

First up is Bryan Eisenberg, co-founder of FutureNow.  ROI, Engagement, Attribution & More.

Attribution:  Apparently Google Analytics inflates search results. What’s working what’s not?  Uses example of a basketball team.  do the players that pass the ball get “credit ” for their points?  Non converting keywords actually may convert as the attribution maybe it influenced later searches.  Analytics will never be purely a science because it is not 100% exact.  It is used for trends.

How are things being reported?  Google only counts the “player” that made the basket, not the ones that contributed.  We are still operating in the dark if we do not understand visitor profiles and do not use personal identifiable data.

Everyone is concentrating on the conversion, without paying attention on the process before conversions.  If it takes 7 weeks to change a button color it is death for companies today.   There has to be flexibility in an organization to make changes and do tests.  An organization has to constantly test over and over.  A contiuous improvement project.

Creating a Marketing campaign, measuring its success is what pretty much everyone does.  However improving campaigns is what is needed.  Amazon.com is constantly adapting, changing and making the experience better.

The process to become more flexible is to have these resources:

Marketing & Analysis
Graphic Design, copywriting, creative resources
Technical

Conclusion:  Measuring Success = Money in the bank.

June Li from ClickInsight.ca: Turning Data into Dollars
Data and Reports don’t make you money.  They only are the beginning of the journey.

Its a conversion funnel:

Data and Reports -> Ask Questions -> Segmentation analysis -> Action -> $$$

The tools don’t provide meaning, the analyst does.  Without an analyst the tool is useless.   An analyst should be involved in the design of how the data is gathered.  Get invited to the design party:

Define Goals -> Design -> Execute -> Cleanse Data -> Analyze -> Decide -> Test -> Assess

What are the behaviors that will be used to measure success? What needs to have extra tagging if the tool isn’t set up to do it by default?

Segmenting Data:  The question to ask is:  “What’s different?”  between people that convert and tose that don’t.  See what is working and what is not.

We see 4 differently shaped funnels,  Web Metrics, Proven Methods for Measuring Web Site Success by Jim Stern.

Work backwards from the conversion event.   sources, keywords, geographies, days of week, what content is being consumed and is there a difference in these segments and how they convert.  Reports are to show if objectives were achieved, Analysis will show where more gains are possible.

We see a case study of a site redesign and go through the metrics of how the website has improve in terms of visits, new visits, bounce rate etc.  Organic conversions increased by 90% but other sources ncreased by 37% so this difference shows that something further can be done..  drille down to keywords and measuring the bounce rate to show what users may be expecting to see on the site.

The important thing is to take action, segmenting gives ou the clues to what you can be doing.  No Action = No Dollars.

Anne Marie Lorriman from Outrider: Search Query Audits — When targeting goes Awry

Exact Query Reporting

Issue #1 = The offside search Result

For example the word “Sonic” can be a toothbrush, a hedgehog, or a DVD publishing company

“Primus” Rock Band, Camping Supplies, or Telecommunications

We cannot anticipate what people are expecting with queries, so you have to go back and check the performance of these Keywords.  Broad match is ok but has to be looked at very closely.  The Quality Score will also go down if the clickthrough rate is not there.   Irrelevant clicks will also cost advertisers:  Monkey Love” is seen on an adwords ad for Ebay, so they are wasting their money for that term.

Issue #2 The hidden defect search result.  If you are bidding on the word “automobile” but only the word “car” appears on your page, your click rate will go up.   So they will create a “car” campaign and an “Automobile” campaign.

Conclusion = An Exact match Query Report with Negative keywords will create a more performant PPC strategy.

Richard Zwicky Enquisite: Analyzing valuable traffic

Data is worthless if not used properly.  Search Analytics is to measure what users have done before coming to your website, whereas Web Analytics encompasses internal traffic behavior.

Organic and Paid traffic behaves differently.  Where do people look on the SERPs page?

Currently Agencies spend 96% of their advertising money on 12% of total return.  Only 50 out of Fortune 500 companies actively do SEO.  When we analyze specific keywords referrals from organic search and segment by geolocation, etc. we can find low hanging fruit.  Example of a california website that wanted to rank for “hotel” in the UK.  They were ranking pretty much everywhere except Londong.  When they noticed this they actively tried to acquire links from local London businesses and the rankings increased for the London area.

Potential =  Keyword Volume/Search Engine Referrals x (Page views) x (Time on site) x (1- Bounce rate)

Then the Q&A discussed attribution of the originating source of a referrer.  I suggested the nooverride function in Google Analytics, but it was pointed out that this will also cause data for repeat visitor sources to be lost.

Pubcon Live Blogging: Analytics and Measuring Success in the Online World

Moderator: Jake Baillie
Speakers:
Richard Zwicky, CEO, Enquisite
Craig Hordlow, Chief Strategiest,
Paul Botto, Head of Analytics Sales, Google
Paul Pellman, CEO, Click Forensics, Inc.

Richard Zwikey

Measuring success in the online world. Richard starts off by talking about the traditional world of analysis, the 1.0 world, and the current 2.0 world.

Web 1.0:

  • Page views
  • Hits lack of standard measurements
  • Undefined ROI
  • Lack of controls
  • Outside of PPC there is an undefined ROI that analytics can’t track effectively.
  • Web 2.0:
  • Provides deeper insights, the 2.0 world represents a new and better way:
  • Transparent measurements
  • Defined, precise ROI
  • Responsible
  • Repeatable
  • Follows your workflow
  • Keyword potential = (1-keyword volume/search engine referrals)(pv)(time)(1-bounce rate)
  • In relation to all other search traffic to the site and conversions:
  • Referral rates – the number of referrals for a given term
  • Conversion rates – the number of conversions a particular term generates
  • Page views – derived from specific terms
  • Time – in seconds that user through a specific term spends on-site
  • Bounce ratio for the phrase

2.0 is information the way you want it (picture of a map overlaid with information)
Use the map overlay to see geographic distributions. Understand how a searcher’s physical location impacts your search results and business.

Web 2.0 analytics allow you to look at very narrow sections of your traffic with respect to all of these metrics. A modern analytics package lets you see data over time and metrics for really specific segments. For example:
hotels, in USA, from Google, page-2 traffic
In this real-world example, looking at a map overlay of only page 2 traffic shows New York and area has a lot of page two Google rankings. Data grids don’t show you this stuff. 2.0 is the mashup of different types of information to gain new or different insight.

Web 3.0:

  • How we collect data might change
  • Channels to reach customers will change
  • How we use the data will change (static and dynamic content creation, reputation management, social media, next?)
  • What we try to accomplish with the data won’t change (branding / sale)
  • How we define value will evolve

Craig is up next:

Craig is going to talk primarily about what he calls “Motive analysis” – this is great because he’s really talking about searcher-intent as derived from the examination of search queries. For some reason this level of analysis often goes overlooked in SEO, and to a lesser extent in PPC.

Are you really, really listening? Marketers have an obsession, keywords: the ‘top’ of whatever. What about the ‘bottom’? The purpose of motive analysis is to dig deep, way beyond ‘top’ this and that.

Motive analysis has five steps:

  • Identify visitor motive through nuances of the search query
  • Segment the queries by motive
  • Analyze the performance of each segment
  • Identify motive disconnects
  • Modify the disconnect on the entry page so it now speaks to that user

Basic necessities: website, spiders, analytics, and a brain

Ten motives of search:

  • Product /service (athletic shoes)
  • comparison/quality – top, best
  • adjective qualifier – white shoes
  • intended use – running shoes
  • vendor/manufacturer – Gucci shoes
  • location – san Francisco shoe store
  • action request – buy shoes
  • instruction – repair broken heels
  • definition – what are pumps?
  • problem – shoes for wide feet

Motive analysis – ranking for these terms is not enough, you must connect with the visitor, software cannot do this for you, people have many combinations of motives.

Use personas: powerful for understanding the user use the 10 motive of search to identify personas. Have a lowest common denominator persona in mind.

least common denominator persona = your mother

Three personas:

  • shopping addict – brand, adjective qualifier
  • local enthusiast: geo “Toronto”, intent “hiking”
  • bargain hunter: intent (walking shoes), price (discount)

Review all referring keywords – start with the websites referring keywords VS entry page.
Begin grouping the keywords at a high level (cheap, discount, sale, bargain, low, clearance all in the same group). High level thematic grouping.

microsegmentation is grouping by highly specific phrases, which enables you to message back with equal specificity. The days of the one word search term are gone.

tip: generate a list of filters and segment. Google analytics example: filter by singular or combinations of keywords

  • geo
  • comparison
  • product name

etc
Save these reports and schedule to run every month

The motive disconnect. When you find a motive that is not performing, it’s a motive disconnect. Usually when your content, value proposition, or business model are not aligned with your visitors.

What do we do about it? Bring it back to the entry page. Ask yourself:

  • Is the message the user wants ont he page?
  • is it succinct and persuasive with more info easily available?
  • is it even feasible foryou to be relevant?(maybe you’re not cheap)
  • is it visible enough
  • should the message be on its own page? (cluttered pages, pages with lack of focus)
  • Rebuild the entry page, build a new entry page.
  • He wants us to build our long-tail (more pages, more!) without letting a motive disconnect occur. Which basically means crafting landing pages that concur with what your searchers are finding you for. I would argue true long tail comes form less structured or less predictable queries

Paul Botto, from Urchin is up next

How do the advanced segmentation features of google analytics relate to what we’ve been talking about?

  • Isolate and analyze subsets of your traffic post-data capture
  • compare segments and key performance metrics side by side
  • analyze your traffic with predefined or customized segments

You can define a segment of visitors who ‘visit this page, then this page, then that page, but don’t buy’ as a comparison shopper. Save that as a segment and view all of those people and only those people.

(GAIQ) Google analytics individual qualification
The course is free, and the qualification is a nominal fee to take the test. This is a new qualification. It’s pretty challenging stuff, so even power users might want to look over the course (I know I will be, though I’m only a battery-powered-user).

Things are not pageview based anymore, it’s an experience like a movie more than a book. Webpronews for example has hundreds of videos. How do you track that? We used to sneak a pageview under the video called (press play on video). The report doesn’t translate well the experience the user had.

Clickforensics similarly has a software demo broken into 12 slides and a ‘schedule a demo’ button – how do we track or learn from the analytics on a page like this? Eeeeevent tracking! Yes, event tracking is the key to tracking these specific non-traditional navigation stuff.

Object, Action, Label

The object is the magazine viewer tool. Actions are turn the page, go to more tools, subscribe, send to friend, etc – The label would be: website magazine august 2008 edition

Google Analytics has a dedicated ‘event tracking’ section now. With top page objects, top object actions, and top object labels. No artificial pageview boosts.

They partnered with adobe, right in flash and flex, you can drop your GA code right into it. Build it into the process flow (like, always tag the play button, and every 10 second mark on the videos). It’s all drop down menu-driven stuff, but you have to get your flash and flex developers implement it.

Paul Pellman is up next

An Austiner who’s freezing his butt off, because today, it’s damn cold for Austin.
Within each keyword you buy there are different levels of quality based on the origin of the traffic. Invalid traffic is more than just click fraud:

Low quality: low conversion rates, cpa too high

Invalid traffic: outside geo, broad match conflict, unacceptable type (mfa, adult)

Click fraud: Viewing invalid traffic over time shows spikes that usually indicate malicious attacks.

Trends: Like spam, bots and botnets are becoming more sophisticated

Almost seventy percent of all sites in google adsense and yahoo are made for ads or parked
22 percent of all invalid activity comes from outside th targeted geo areas
Competitor clicks deplete ad spend
Brand infringement violations use established brands to send customers to competitor’s sites

Q and A
Comment more than a Q: Nobody talked about crazyegg, quicktale, and pagealyzer – allow you to see the actions of individuals in a page, how long do they take to fill out forms, poor man’s heat maps

A: beyond what happens on a page, identifying the opportunity for potential on a site as a whole is the next phase.
The vast majority of ppl using analytics are barely scratching the surface of what we have now – it’s not a technology problem, it’s a methodology problem. They want out of the box, ooh pretty reports, what needs to be updated is methodology.

Q: i get about a 17% invalid click rate – is this recognized by google analytics?

A: google analytics is not the right tool to analyze invalid clicks – but it is tied to adwords, so we pull that data out automatically. We update your analytics report to show exactly what you actually paid for.

Q: object action labels, are they available in google analytics now?

A: event tracking is invite only at the moment

Q: the tracking cookie in analytics is six months, isn’t that a bit long?

A: there are several cookies actually, placed with different time frames associated, so this could be a big long discussion. There is logic behind choosing those time frames, and adding the ability to change them is worth considering, but for now the choices are a best fit for analytics users as a whole

Q: its my understanding that the google analytics API is still in very private beta – is it opening up any time soon?

A: i’m not here to announce anything, if you give me a card i’ll get back to you. It’s an a exciting one, the API should be exciting for a lot of people here.