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How To Promote Your Online Visibility Using Web Analytics. How To Promote Your Online Visibility Using Web Analytics.
 

How To Promote Your Online Visibility Using Web Analytics. How To Promote Your Online Visibility Using Web Analytics.

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  • Hi all. For my es a privilegy and a pleasure be here in Iran.
  • OK lets go to start I have divides the presentations in 7 blocks. For my the objectives of today is all you understand the crtitical implementation you have to do in Web analytics,
  • Those of us who started working on Analytics in 1996 had to fight with counters and log analyzers. Do you remember the counters ? It was a great achievement when we could say: My page has had 33.000 visits …and we were very proud. At those times the world of Analytics was dominated by IT people . The only ones who had access to the servers and data . And you could do nothing without passing through them. It was a terrible situation, far away from the marketing analysis we were looking for . And by the way it was also what the marketing people (and the CEO) were looking for.
  • But analytics is useful to understand what has to be measured. You have to bear in mind that all the different online business models share the same scenery. We ha ve to define a clear objective of what we want to do on our page. And then of course we will need traffic and visits to our website to be able to achieve that objective . What happens on site? Visitors are initially equal to possible conversions. On a second step most of them leave after visiting a few pages , and without converting . On the final step we normally receive only a few conversions . These conversions are our objective, and naturally our business goal will be to obtain the larger possible number of them. For this we will need to understand the behaviour of our user. As I said before to be able to do this we need qualified traffic , so don ’t forget about that. Without enough traffic we might never reach our business goal, no matter how much we improve onsite conversions.
  • “ Web Analytics is the measurement, collection, analysis and reporting of Internet data for the purposes of understanding and optimizing Web usage”. The Official WAA Definition of Web Analytics Ours: Web Analytics is a speciality of online marketing that deals with the measurement, collection, analysis and reporting of internet data for all online agents related to a give online activity. The purpose of Analitics is the understanding and optimizing of online business .
  • But to understand how the user behaves, we must take into account more factors than just the click stream. Click stream only gives us the quantitative measurement of behavior. We must also take into account the qualitative data we obtain from usability testing, interviews, focus groups, and eye tracking studies. It is useful to consider user navigation recording, the monitoring of users, as to how the user actually navigates. It is also important to note the importance of developing comparative scenarios to assess how the user behaves with different messages and offers. This is A/B or multivariate testing . Finally you should always compare yourself with competitors. This can be done using a wide number of commercial tools All these disciplines are part and should be included within the work of a web analyst .
  • This block is intended to explain to the basic aspects of web analytics. Starting on how data is collected, definitions, importance of the code, and so on.
  • I will start with an explanation that is somewhat technical but it is very important to understand how data is collected. There are two basic ways of collecting data, logs and tags- though some systems use a combination of both methods. Tags work through cookies that are stored on the user ’ s browser . No doubt the measurement via tags is much more comprehensive and accurate specially measuring unique visitors. But it also has limitations: if I use 5 browsers, each time I access a page with a different browsers, I ’ m a different user. By contrast, analytic via log, feeds on the information generated in the server log file, and is unable to collect certain data at the level of recurrence and user identification . Measurement via log is used by all hosting providers because they have automated processing through free programs such as Awstats, Analog or Webalizer. Until Google Analytics started to be popular, the use of logs was the most common measurement system. Nowadays I have to clarify that the measurement using cookies (tags) is much more reliable, especially when measuring unique users . It is now the industry standard. What interest me, is for you to understand that there are two methods of data collection. Each has its pros and cons and there are also hybrid tools like Urchin Software, but the actual standard of measurement is through cookies.
  • This is the code that is included in the pages and is responsible for collecting the information. Depending on the peculiarity of the page this code should be changed or customiz ed. For example, if you want to measure different domains or sub domains (pressroom.overalia.com overalia.com ... etc) or measuring file downloads. Although analytics via tags is Plug and Play, you need to consider some important aspects of implementation.
  • But let's see quickly how GA works (or other tools that use the same technology). Basically when a user makes a request to a web page, the JavaScript code is executed, leaving a number of cookies (tr aces) in the browser. The information is sent to Google where it is saved in a text file (a log). GA processes the data, applies a series of filters and creates reports. These reports are stored in a database and shown in the reports by default. As mentioned before, if you personalize the data collection through the code, you will have richer information As you can see it is basic to spend time and effort making sure data is collected properly. If we don ’t understand this, probably the reports will not be as accurate as they should
  • If there is a PDF document, flash or video piece on the page, the default code for Google Analytics can not collect that information. It will be necessary to label them specifically so that the information can the collected by the system.
  • It is important to understand the differences between metrics and dimensions. And that is because it is the way to cross data from Google Analytic ’ s interface. Dimensions are characteristics of your visitor or your site, determined before the visit began (an exemple are time on site, pages views per visit, calculate conversions by email campaign Metrics are values calculated for that visit , and are always a count or a ratio (10 pv per visit or 10 conversions)
  • Until now everything seems to be a technical problem. But I want to stress the importance for business and marketing people to understand a minimum of technical aspects to be a valid interlocutor with the technicians. I could like to conclude this part repeating that it is very important to define well needs before measuring. And that establishing the right setting for the code is the key for the collection and customization of information.
  • The most important idea I want to convey in this section is that before you measure you must define goals if you want more information than just page views and visits.
  • This is the website for one of our clients who print albums and calendars for consumers. Everything is done on line. It is a do it your self website (upload the photos, layout and complete the album) The definition of objectives (goals) is the most important issue when implementing a measurement system. In this case is sales albums. You can fix them to measure pdf ’ s downloads, subscription to newsletters, contacts ... and assign economic valu es ​​(eg. Each catalog downloaded from Iran has a value of 200 €) You can also assign objectives to qualify the traffic (per exemple 10 pv/v or time on site)
  • So what is a goal? In Google Analytics, a goal represents an activity or a level of interaction with your website that ’ s important to the success of your business. Some examples of goals are an account signup, a request for a sales call, or even that the visitor spent a certain amount of time on the website. There are three types of goals in Google Analytics: A URL Destination goal is a page that visitors see once they have completed an activity. For an account sign-up, this might be the “ Thank you for s igning up ” page. For a purchase, this might be the receipt page. A URL Destination goal triggers a conversion when a visitor views the page you ’ ve specified. A Time on Site goal is a time threshold that you define. When a visitor spends more or less time on your site than the threshold you specify, a conversion is triggered. A Pages per Visit goal allows you to define a pages viewed threshold. When a visitor views more pages –or fewer pages –than the threshold you ’ ve set, a conversion is triggered. Event tracking goal
  • But what really is important is to create Landing Pages aimed at the achievement of objectives (goals). This is an example of one of our customers: a bank. Here you can see that the goal is the sale of a fixed term deposit with a 3% interest. And it can be contracted through a form or calling a commercial agent through real tim e video online.
  • In order to monitor the effectiveness of these action-oriented designs it is necessary to use funnels to determine the effectiveness of these designs. Defining a funnel is valuable because it allows you to see where visitors enter and exit the conversion process. For example, if you notice that many of your visitors never go further than the “ Enter shipping information ” page, you might focus on redesigning that page so that it ’ s simpler. Knowing which steps in the process lose would-be customers allows you to eliminate bottlenecks and create a more efficient conversion path. A funnel is the set of steps, or pages, that you expect visitors to visit on their way to complete the conversion. A sales checkout process is a good example of a funnel. And the page where the visitor enters credit card information is an example of one of the funnel steps. So, the goal page signals the end of the activity – such as a “ thank you ” or “ confirmation ” page – and the funnel steps are the pages that visitors encounter on their way to the goal.
  • This is an exemple of a tax office in our of Govermment clients We track the process of download a certificate document.
  • This is a new feature that helps understand the functioning of the objectives by Flow charts, where you can see the behavior of traffic sources for each target
  • Ultimately I want to convey that the definition and goal setting is the principal and most important part to work with a web analytics tool. Without defining them is very difficult to work well. Aware of this Google has 4 different functions to: • Be able to calculate the rate from visit to conversion (and apply a value to that rate) • Create multi channel funnels to understand the behavior of the sources of traffic acquisition • Viewing data through funnels or flow charts • Import goals into Adwords
  • Finally to close the chapter dedicated to objectives I would like to outline some of the indicators we use to manage them. This point is very important to make decisions on what works and what does not.
  • It is very important to identify and work on the different profiles of potential customers who you want to attract to your website. Basically because: • It will be much easier to personalize better the content of your website and therefore you will have more options to improve the conversion rate • It will help you defining your media plan and advertising spend, based on those profiles. • Take the case of a package delivery portal designed for individuals, were we have a clear target audience in Erasmus students. For them we have defined personalized content to try to attract their interest. We include advertising and sponsored tweets for this group to show that this website has the lowest prices in the market. They can tell their mothers and grandmothers to send food using this service! Expatriates are another segment of users that is very clear.
  • Apart from other types of user segmentation we will see later, one of the possibilities that I like more to identify and target users are the customized variables. Segmentation allows you to create user types at single-user level, the behavior of the visit or page view. In the example of our package delivery portal it means that we could see which users who have seen prices and that have been customers have registered and have finalized a shipping quote. This information is extremely powerful because you can better understand what users do when they land on your website. For analysis it helps to divide them in group behaviors to draw conclusions. Clients or not clients, loged or not loged …etc
  • The next report you needed is the one for the internal search engine. You will learn what the user wants to find on your site, what he is looking for and has not found in the conventional navigation. You will always learn curious things that surprise you. Users are unpredictable. One of the biggest mistakes in analytics is not having activated this report.
  • This point is one of the most complexes to implement. It relates as to how to generate qualified traffic based on the objectives we have defined and given that we know who our potential customer is. Based on this premise we have to define different content pages that receive that traffic to try to turn them into customers. For this reason we have to define and design different entry points for each objective and use visualization of the behavior of these page routes to understand what works and what does not work for each traffic channel acquisition (using funnels and Flowcharts)
  • The most important setting of all is to integrate Google Analytics with Adwords. That is the most direct and fastest source to generate traffic, with a cost. This is done linking both programs. This allows you to analyze keywords sending traffic, sites & campaign & ad variation and tracking (when properly tagged). No program has this level of integration at campaign level.
  • The next rule of thumb is to label all campaigns. If not labeled Google Analytics will see all traffic come as a referral (a link from page A arrives to page B). However if you label all campaigns you can trace the effectiveness of this source in most reports and thus know if it converts and how that traffic behaves. Remember the example of the need to get traffic coming from students in Erasmus. The easiest way to do this is to use the URL builder: an online form where you sign up the landing page of the banner. Then what you do is add parameters that are the name of the campaign, if it is a banner or PPC, and if you use different ads. It ’ s really simple and effective. Most important things to remember when labeling campaigns are: • Tag everything: cpc, cpm, social, email, newsletter, mobile, etc. • Be consistent: create a shared naming convention • Prepare for great analysis: Annotations & Advanced Segments
  • Also keep in mind that the traffic generation process is very costly in terms of investment. It is therefore highly desirable to unify the planning of traffic acquisition (pre-click) with what happens on page after (post click). The landing page testing using Google Website Optimizer (and other solutions on the market) is the formula to learn how to improve traffic acquisition by testing content. In this example for our client we tested different looks and feels of the same page to learn which one is better for the user sign up. The campaign was for a contest sent by mailing to thousands of users. We recommend starting with simple tests (which are called A / B testing) that afterwards can be complicated by testing many of the sections that make up a page (a section, a text, an image).
  • This is one of our French customers. They are dedicated to selling children ’ s clothes fashion oriented and at a very good price. They are present in 5 countries with over 250 stores and online. They belong to a major corporation and the company is a very small part of a corporate giant, The Mulliez Group. Every week they introduce 100 new items in their catalog
  • The conclusion to this section is that is not just about having the budget for traffic acquisition, it is to understand that we have to create very flexible and agile organizations, where to move a byte can not be a trauma ! I put this example of the elephant and the mouse as a major error that some companies act like elephants. They are slow in making and implementing decisions. The thing is to try to convert these elephants in mice to be nimble and quick. Change what does not work and be much more effective than the competition. This is the difference that marks a successful online business. It is NOT a change in technology. It is a cultural change.
  • One of the improvements Google has worked on is to offer continuous improvement in the segmentation of information. It is one of the most powerful parts of GA If you work with data segments (either by source of traffic acquisition, user segment or in sections, product families .. etc), it is much easier to achieve improvements that if you work in aggregated form with all the info of the site. It is therefore necessary to work on the basis of planning and prioritization of improvements but based on segments. In our example of price comparison for parcel shipments, we are considering planning a campaign to increase 48% organic traffic based on a series of searches that we know have a lot of traffic to our competitors and we do not receive. And in parallel we are working on campaigns to improve the results of the expatriates working in other countries who reside outside of Spain.
  • This is the list of the main tools for segmenting the information in GA. They are really important and you need to know them and use them to implement everything discussed above. The main functions are: User segmentation we ’ ve seen before using the set function var The simplest segmentation is the one done at chart level using dimensions and metrics to filter the information. Segmentation based on profiles and filters (the most potent of GA). It allows you to analyze part of a site (for example languages ​​or traffic sources) and have the vision of unique users who have accessed to that set of pages We also have advanced segments and custom reports that are also very useful and easy to implement in the reports themselves.
  • The conclusion and the rule of thumb is that you must understand that the success of your online presence is based on trial and error. Or what we say: the sooner you get it wrong the better. The acquisition of traffic is extremely costly in terms of resources and energies. It is therefore important to understand that apart from working the discipline you need to convert that traffic and then try to retain it to all to capitalize your marketing efforts Without these 4 steps (define objectives, identify users, generate traffic and convert) this process is much slower and more expensive. The tools and features we have discussed are the starting point, but do not guarantee success. 90% is about having talent. Online marketing has much of a science but still more of creativity and art.
  • In this block, the idea is to explain that the online situation has changed. We have evolved from having one website for our business to have multiple online properties. This has it is consequences in the work that's involved in management, maintenance and revitalization of the properties. The reason for this change is that we must be where the customer is. And the customer is now in many different places From the analytical point of view this is a problem as now you have to consider many different data sources (social networking profiles, images, video, twitter ... etc). But from the standpoint of business it is an opportunity because we have now more chances of reaching our potential customers.
  • And we have changed from measuring only one variable - counting pages and views - in our outdated corporate Web sites to a new environment much more complex from the point of view of information management
  • And basically this new environment is defined by the guru Avinash Kausik (Evangelist of Google Analytics) and is what is called Web Analytics 2.0 Avinash defines the following 6 points, the sum of which must be taken into account to improve online presence and make it more effective. Clickstream-The What: what we have been doing until now 2. Multiple Outcome Analysis-The How Much : The Clickstream is no longer enough. There are many more sources of data (the mushrooms ....) 3. Experimentation & Testing: The Why. By trial and error you can find many answers. 4. Voice of Customer: The Why. All those quantitative data that do not answer a question can be interpreted by relying on qualitative data from users via surveys or user dynamic 5. Competitive Intelligence: The What Else. This is extremely important. We could give a full day talk about this. The question is finding out who is doing well. And try to learn with the appropriate tools all their strategy details. It's not about starting from scratch. 6 . Insights: The Gold! And finally the sum of all these tools and disciplines account for Insights. The information needed for decision-making. The road map to improve your online presence. Without subjectivity.
  • Avinash suggests a number of tools for each stage. My recommendation is that there is a risk of paralysis by analysis. If you try to measure everything and at the same time, the work is resource intensive. Depending on your experience, you must dose the use of these tools . The important thing is to have a plan based on the thumb rules that we discussed earlier. The tools help a lot, but they are not that important. Your talent is more important
  • Given this complexity of over-saturation of data and sources, the priority to be able to handle all these scenarios is simplification. The roadmap to drive our project on line, the Insights: The Gold, that Avinash describes, has to be simplified to 8 indicators. We must not and can not work with many more. It is therefore very important to understand that the great challenge for analytic is the simplification of the scenarios. And the representation of this simplification should be done in a good dashboard.
  • What gets measured gets managed – but - It is important to understand how to simplify the presentation of information so that a few data gives us much information. Key performance indicators are designed to summarize meaningfully compared data.
  • It is important to differentiate between the tool reports and other you can create. Like entering data for the contact objective you had for that period and thus enrich the reports. I always recommend working with data of line based on the result that we had planed. Some features and recommendations to represent data in dashboards are: • Indicators show always comparison over time. • The representation helps much : Green is good , red is bad , yellow is getting bad • Indicators trending up have up-arrows; Indicators trending down have down -arrows • Always show the percent change from reporting period to reporting period Finally it is important to note the units of measure with which we work: averages, percentages and averages and ratios. These units of measure can be used in all fields of dimensions and metrics available and includes GA.
  • These are some of the most commonly used averages:
  • These are some of the most commonly used percentages
  • These are some of the most commonly used percentages
  • In Summary: Although averages and percentages are powerful metrics, rates and ratios are the numbers most commonly associated with key performance indicators. The most commonly discussed indicator of all is inarguably “conversion rate” which is actually dozens of different numbers depending on your business model and information need. Rates help you understand the percentage of visitors who start processes actually finish. Ratios are more typically more complex. I chose to treat rates different than percentages due to their common usage in industry—people talk about “conversion rate” not the “percent of visitors who completed such and such process.”
  • From the business point of view this is a representation of what are the tasks to implement a web analytics project. The first step is to write a business document . To have the business objectives clearly identified. This point needs to involve project and marketing managers. Having documented the most important point in the Business Definition Requirements (BDR), we suggest a series of training sessions for those profiles that are not used to working with data or don ’ t know web analytics in depth. This training is very useful for normally it is also a source of new ideas that complement the DBR. Keep in mind that the people working in the project are those who better know the business and the potential customers. After closing this reflection process, we can write an Operational Document with the primary and secondary objectives: macro conversions and micro conversions. This document will be the base for all reports and most of the configuration. We will also need to define another document called Technical Business Requirement . That is the adaptation of the document to a technical language environment. It will describe the configuration requirements of the code and the labeling of the pages so that business objectives are fully measurable. This is important because without a good analysis, we run the risk of not having accurate information. Finally, the process goes through a review of work done and qualitative analysis of the data. It is useful to have a second training day for the presentation of data, reports and dashboards. It is important to provide support to users who are not accustomed to working in these environments.
  • This slide is to emphasize the absolute need to document the entire process. This must be done for the whole process: from the business part to the implementation. It is highly recommended to document the configuration done, with change control and with one person responsible. Users can not touch the settings without the administrator permission.
  • For a simplified view of the process we can divided it into three phases: • Definition: business objectives and translating them to a measurable environment • Implementation: translating these objectives to design the technical solution and train users • Post implementation: ensure that data is collected properly and that the data make sense. Try simplifying them when possible. It is important to add the importance of customizing reports and distributing them based on peoples roles. Each user should receive only what adds value

How To Promote Your Online Visibility Using Web Analytics. How To Promote Your Online Visibility Using Web Analytics. How To Promote Your Online Visibility Using Web Analytics. How To Promote Your Online Visibility Using Web Analytics. Presentation Transcript

  • Guillermo Vilarroig Ceo and founder 3th February 2012 Overalia is certified partner: How To Promote Your Online Visibility Using Web Analytics.
  • 3. The most important thing and the rule of thumb 5. Manage information through metrics and indicators 6. Work methodology 2. Keys to understand the basics 1. What is - and what is - not Web Analytics 7. Conclusions 4. There's more ... The Mushroom Theory
  • b. Understanding what has to be measured c. Types of measurement (qualitative and quantitative) d. Web Analytics definition a. Counters in 1996 1. What is - and what is not - Web Analytics
  • - what is not - web analytics Pantallazo de la herramienta webalizer A counter ! In 1997 counters were fashionable They counted visits... Fortunately they lasted very little time ... In 1994 was when the first log analyzer appeared. Free tools Analog, Awstats Webalizer are examples. Webtrends is the tool that leads the market.
  • b. Understanding what has to be measured Visitors = Possible Conversions Exits Exits No exits Conversions AMAT (acquisition, measurement, analysis and testing)
  • “ Web Analytics is the measurement, collection, analysis and reporting of Internet data for the purposes of understanding and optimizing Web usage”. The Official WAA Definition of Web Analytics d. Web Analytics definition
  • c. Types of measurement (qualitative and quantitative) Fuente: Dave McClure
  • c. Definition of visits, user, etc. pages viewed, etc. d. More code for further needs: event tracking and e-commerce e. Understanding the metrics and dimensions f. Conclusion: it all starts with the code 2. Keys to understand the basics 1. What is - and what is not - Web Analytics b. How data is collected and how Google Analytics works a. Types of data sources (logs and tags)
  • a. Types of data sources (logs and tags) User Page Server Log Analytics software Analytics software User Page Server Tag 1 2 3 2 3 1 2 3 3 4 LOGS TAGS
  • b. The importance of data collection
  • b. Google Analytics - how it works Scheme by Justin Cutroni ::
  • The importance of cookies in analytic systems based on tags
  • In Google Analytics, a pageview is counted every time a page on your website loads. So, for example, if someone comes to your site and views page A, then page B, then Page A again, and then leaves your site -- the total pageviews for the visit is 3. c. Definition of visits, user, etc. page viewed, etc . Source: Google
  • A visit -- or session -- is a period of interaction between a web browser and a website. Closing the browser or staying inactive for more than 30 minutes ends the visit. For example, let ’ s say that a visitor is browsing the Google Store, a site that uses Google Analytics. He gets to the second page, and then gets a phone call. He talks on the phone for 31 minutes, during which he does not click anywhere else on the site. After his call, he continues where he left off. Google Analytics will count this as a second visit, or a new session. Note that throughout these modules, the words “ visit ” and “ session ” may be used interchangeably. Source: Google
    • From last august, some rules has changed:
    • The visit will restarts when the source changes
    • At the end of the day
    • More than 30 min between pages
  • A visitor is uniquely identified by a Google Analytics visitor cookie which assigns a random visitor ID to the user, and combines it with the timestamp of the visitor ’ s first visit. The combination of the random visitor ID and the timestamp establish a Unique ID for that visitor. You ’ ll learn more about the visitor cookie in a subsequent module. Source: Google
  • Generally, the Visitors metric will be smaller than the Visits metric which in turn will be smaller than the Pageviews metric. For example, 1 visitor could visit a site 2 times and generate a total of 5 pageviews. Source: Google
  • d. More code for further needs: event tracking and e-commerce – Event tracking
  • d. More code for further needs: event tracking and e-commerce - Ecommerce example Parcel shipment search engine on line E-commerce
  • Metrics & Dimensions Dimensions are characteristics of your visitor or your site, determined before the visit began Visitor Visitor Characteristics (dimensions) Pages Actions (metrics) Page Characteristics (dimensions) Each page on your site has certain information that describe it, too As that visitor begins to act on pages, their actions are counted and calculated in ratios 1 2 3 Metrics are values calculated for that visit, and are always a count or a ratio
  • f. Conclusion: it all starts with the code
  • 3. The most important thing and the rule of thumb a. Define very well your sales proposal and objectives b. Identify who are your potential customers 2. Keys to understand the basics 1. What is - and what is - not Web Analytics e.Conclusion: Do not stop the Music. Trial - error. c. Generate traffic by the various acquisition channels d. Segment and divide the information. It will be much easier
  • Define your sales proposal and objectives Identify your potential customers Generate traffic ( acquisition ) Segment and divide the information Don't stop the music
  • a. Define very well your sales proposal Do you have a plan?
  • Define very well your objectives There are three types of goals in Google Analytics. A URL Destination goal is a page that visitors see once they have completed an activity. For an account sign-up, this might be the “ Thank You for signing up ” page. For a purchase, this might be the receipt page. A URL Destination goal triggers a conversion when a visitor views the page you've specified. A Time on Site goal is a time threshold that you define. When a visitor spends more or less time on your site than the threshold you specify, a conversion is triggered. A Pages per Visit goal allows you to define a pages viewed threshold. When a visitor views more pages --or fewer pages --than the threshold you've set, a conversion is triggered.
  • Object-Oriented Design
  • Use redirections Form Confirmation Landing
  •  
  • Source: Google
  • I recommend the original post in Google Analytics offcial blog
    • Having decided on a measurable objective, it is advisable to establish indicators to facilitate monitoring of the target.
    • If the objective is, for example, increased contacts through the web site, we can generate as many indicators as we wish:
      • % conversion of contacts made
      • Cost per contact
      • Cost per contact per traffic source
      • % contacts per traffic sources
      • % contacts per users per geographical area
      • Effectiveness ratio per campaign
      • Contact objectives compliance for Q1
      • Etc.
    Indicators for objectives
  • b. Identify the profile of your users Understanding the acquisition and quality of the traffic * User behavior and quality vs traffic type User effectiveness that come from social networks Effectiveness from direct traffic and branding (via Seo) Effectiveness from paid traffic (agregated campaigns) Effectiveness from Adwords traffic Effectiveness traffic from off line campaigns This data is shown aggregated in a comparative chart
    • User segments with greater visits Recurring By type of profile (young, elderly, disabled ...) By Type of Content
    * User behavior and quality vs traffic type The traffic quality is defined based on a number of technical parameters, such as the length and depth of the visit and the objectives achieved.
    • Define multiple tracking segments based on visitor, session or even webpage-level interactions in order to collect site usage data in ways important to your business.
    Customized variables _setVar() Naming Architecture is necessary since they can overwrite each other 3 Scopes: Visitor, Session, and Page | 5 Slots per Page Slot Visitor Session Page 1 Member 2 Demographic 3 Logged In 4 Saw in-site ad 5 Page Category
  • Understanding what user wants to find on your site, and has not found
  • c . Generate traffic by the various acquisition channels Do you have a plan? Create a media plan and get in wrong, the sooner the better How are you going to attract traffic that converts to client ? Remember search engines, display, affiliates, e-mail Marketing…combine them all
  • Adwords integration with con Google Analytics Dimensions
  • Label all campaigns http://www.google.com/support/analytics/bin/answer.py?hl=en&answer=55578 http://www.xx.xx/index.php?utm_source=netaffiliation&utm_medium=afiliacion&utm_campaign=campaña1
  • Client: Sci Fi channel NBC Universal Studios Spain Objective: sign in to take part in a competition Result : 102% better Test with Google Website Optimizer
  • An example
  • Elephants and mice; a cultural change Organizations are sometime too slow
  • d. Segment and divide the information. It will be much easier It is easier to work with segmented data. Campaigns, types of users, content, etc. .. CONVERSION RETENTION ACQUISITION
  •  
    • Very interesting to give access to part of the site
    • It allows us to access only the information we need
    • Filters segment data (eg, access only to the press room)
    • Filters
    • Insights
    • Filter the data according to your needs
    • Data collection begins once the filters are applied to the data.
    • There are predefined and custom filters
    • There is no turning back.
    • Recommendation: to have a profile with all data
    Profiles and filters
  • Filters on profiles
  • Advanced filters for punctual analysis
  • Creating segments the easy way. An example
  • Customized reports Each user has his own custom reports and can put then in his personal panel or have them sent to his mail in certain formats on a scheduled basis.
    • define objectives
    • identify users
    • generate traffic
    • convert
    e. Don ’ t stop the music trial and error CONVERSION RETENTION ACQUISITION
  • 3. The most important thing and the rule of thumb a. From click stream to web 2.0 2. Keys to understand the basics 1. What is - and what is - not Web Analytics 4. There's more ... the Mushroom Theory b. Mushroom measurement c. Dashboards
  • The Mushroom Theory From one website to multiples websites
  • a. From click stream to web 2.0 Before it was just a matter of counting pages Fuente: Avinash
  • b. Mushroom measurement The complexity of analytics 2.0
  • b. Mushroom measurement The complexity of analytics 2.0 Fuente: Avinash
  • c. Dashboards A dashboard is a visual display of the most important information needed to achieve one or more objectives , consolidated and arranged on a single screen so the information can be monitored at a glance .
  • 3. The most important thing and the rule of thumb a. Percentages, rates and averages. Bibliography 2. Keys to understand the basics 1. What is - and what is - not Web Analytics 4. There's more ... the mushroom theory 5. Manage information through metrics and indicators b. The importance of dashboards c. Conclusions
  • KPIs help to get insight in your business performance "What gets measured, gets managed ” . Key performance indicators are designed to summarize meaningfully compared data.
  • Differences between reports and KPIs Key performance indicators are always rates, ratios, averages or percentages; they are never raw numbers . Raw numbers are valuable to web analytics reporting to be sure, but because they don ’ t provide context, are less powerful than key performance indicators.
    • Indicators always show comparison over time .
    • The representation helps a lot: Green is good, red is bad, yellow is getting bad
    • Indicators trending up have up-arrows; indicators trending down have
    • down-arrows
    • Always show the percent change from reporting period to reporting period
    • Set thresholds and show warnings
    • Set targets for improvement and report against those targets
  • Used Averages
      • Some interesting web analytics averages:
      • Average Page Views per Visit
      • Average Cost per Visitor
      • Average cost per visit
      • Average cost per conversion
      • Average profit per user
      • Average profit per visitor
      • Average CTR for each payment campaign
      • Average internal searches per visit
    The importance of establishing indicators for actions
  • Percentages
    • Some percentages of interest for web analytics:
      • Percentage of new and returning users
      • Percentage of new and returning customers
      • Percentage of users segmented (by source of traffic, location, etc..)
      • Percentage of visits whith little, medium or long time on the site.
      • Percentage of visits with little, medium or many pages viewed on the site.
      • Percentage of visits with low, medium or high frequency.
      • Conversion rate of visitors (or customers) new and returning
      • Percentage of users who use search.
      • Percentage of search pages with null results.
    The importance of establishing indicators for actions
  • Rates and ratios
    • Some rates of interest forvweb analytics:
      • Conversion rate for orders
      • Conversion rate of new registered users
      • Conversion rate of new and returning users
      • Conversion rate segmented (by source of traffic, location, etc..)
      • Rate of initiated shopping carts
      • Rate of completed shopping basket
      • Rate of data downloads
      • Rate of forms sent
    The importance of establishing indicators for actions
    • Eric T. Peterson - The Big Book of Key Performance Indicators
    My Idol Bibliography
  • 3. The most important thing and the rule of thumb 2. Keys to understand the basics 1. What is - and what is - not Web Analytics 4. There's more ... the mushroom theory 5. Manage information through metrics and indicators 6. Work methodology Conclusions
  • Consulting Definition of objectives Global Analysis Report * Reply to business questionnaire and address specific questions
    • Decisions and tasks client / consultant
    * Distribution of reports * Revision and quality control Tag pages * Support in the page tagging Set up the code * Customize the code
    • *Collect users data. Definition of indicators.
      • Report Definition
      • Dashboard Definition
    Training Sessions Training+ Support + Follow up
  • Translate the goals to the tool
    • Business Section
    • Collection of information and objectives
    • Translate goals to a metric environment
    • Define indicators
    • Technical Section
    • Definition of label variables
    • Special specifications for some reports
    document that sets out the reporting needs document containing the code configuration for all pages
  • IMPLEMENTATION POST - IMPLEMENTATION DEFINITION
    • Define business goals
    • Move to a metric environment
    • Document
    Define
    • Design the technical solution
    • Customizing the code
    • Document
    Design
    • Put the code in the pages
    • Check that the code works well
    Implement
    • End user training
    • Experience and work with the tool
    • Make the most out of it
    Assimilate
    • Analyze reports
    • Improve, customized reports to improve results
    • Semi-expert user
    Optimize
  • Common mistakes
    • I would like to comment on the most common mistakes,
    • based on our experience for the past 12 years:
    • Don ’ t label (all) campaigns or define objectives
    • Don ’ t work with redirects (funnels) ...
    • Non-optimized URLs and titles ... (or too much optimized ...)
    • Wrong structure and nomenclature of the directories ...
    • B read crumbs not be well implemented ...
    • consequences of working with domains and subdomains ...
    • Not labeled (onclic) PDF documents, office, zip ’ s ...
    • Label (event tracking) flash, ajax, videos…
    • Allow a "free" profile without applying filters
    • Don ’ t link GA account with Adwords
    • Don ’ t record broken links and error pages (client 4x and server 5x)
    • Don ’ t work with annotations
    • No segment information ... terrible!!
    • Don ’ t do content testing (if you want to improve) ...
  • 3. The most important thing and the rule of thumb 2. Keys to understand the basics 1. What is - and what is - not Web Analytics
      • Conclusions
    5. There's more ... the mushroom theory 4. Manage information through metrics and indicators 6. Work methodology 7. Conclusions
      • Define one page Business Model with:
      • Customer segments
      • Desired actions and behaviors
      • Identify critical
      • Conversion Events and
      • Dashboards for each segment
      • prioritize
      • Test and develop Marketing Channels
      • measure volume
      • measure cost
      • measure conversions
      • Optimize product and marketing using
      • Fast Iteration cycles
      • A/B testing
    Fuente: Dave McClure
  • The city where I live
  • Great small gastronomy called “ PINXOS ”
  •  
  • Merci Guillermo Vilarroig [email_address] #g_vilarroig