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When web analytics data becomes more integrated to company's enterprise data, it becomes even more critical to manage the data integration. In order to reflect consistent integration and expectation of reporting outcome, web analytics and other data need to be properly managed through different iteration of version changes within the Business Intelligence (BI) system.

For example, your web analytics might be integrated to your Microsoft SQL server, Oracle, SalesForce, or other enterprise solution; you could be feeding site visitors from your web analytics tool and run it against sales or market data. (CRM and supply chain data integration with web analytics are pretty common in ecommerce.)

When your BI solution goes through different changes or version releases you got to make sure the joins and data integrations aren't affected by it. In my experience, common challenges are filter requirements or scalability of data across multiple sources due to difference in definition of data and its application within the original source.

Good example of this is reporting different sales regions. You can apply different data attributes to identify regions. Here are some examples:
Page tagging values like Country code, Cities, Continent, Regions (AMR, EMEA, APAC), web analytics visitors data based on IP address, language ID, etc.

So when you mesh two data from different sources, using CRM and web analytics data as an example; CRM data may have user profile for where they reside (e.g. California), and web analytics data may feed traffic data based on country/language value tagged on the page (e.g. us-en). What that means from BI integration perspective, you need to have mapping table that maps California with us-en, so BI reporting will properly scale to recognize two data sources when users select "USA" from the BI reporting.

This example was a simple one, but it gets more tricky when different sources are involved (imagine when you have different subdomains or data managed by 3rd party, that you want to integrate...).

My point is, depending what the business goals and reporting needs are, you need to be careful, well planned, document the requirements, caveat the data, and do what ever it takes to not waste resources so at the end of the day you're not spending more resource than the value that will be expected out of the BI solution. Why I am saying this when it should be a project manager's work and not analytics analyst? At the end of the day you're likely to work with project manager to feed web analytics data (possibly other sources of data, too), and web analyst will be doing the analysis out of that BI solution and be accountable for that reporting/analysis.

All of that careful planning and execution makes web analyst valuable when involved in such BI projects, and got to be accountable for the reporting end when you use that data as an analyst. You definitely don't want ad hoc changes and poorly managed change management process to affect your analysis work. Good data coming into Web Analytics tool and feeding good data to BI solution can still yield bad data going out.

"Great data in Garbage out" is possible when you don't have the right change management or poorly planned BI solution.

When I talk to various experts in the industry, it is common to find few companies that do all of these integration with ease. If there is a company that did that well, a lot of props go out to them, and I bet they went through many challenges with many sweat and tears.

As web analytics get more sophisticated and integrated with many business data, web analysts will need to be more wise and educated in this field of data management.

Definition of change management (from Wikipedia):
Change Management is an IT Service Management discipline. The objective of Change Management in this context is to ensure that standardized methods and procedures are used for efficient and prompt handling of all changes to controlled IT infrastructure, in order to minimize the number and impact of any related incidents upon service. Changes in the IT infrastructure may arise reactively in response to problems or externally imposed requirements, e.g. legislative changes, or proactively from seeking improved efficiency and effectiveness or to enable or reflect business initiatives, or from programs, projects or service improvement initiatives. Change Management can ensure standardized methods, processes and procedures are used for all changes, facilitate efficient and prompt handling of all changes, and maintain the proper balance between the need for change and the potential detrimental impact of changes.

In blogosphere, I often read about discussions on what could be the best web analytics dashboard, or that one best KPI. In reality, there is no such thing as a perfect dashboard that meets everyone's requirement. The dashboard will be catered to someone who just needs to know the bottom line, who could be the decision maker, most important person in the company or team, etc. With various business units supporting the entire online business, it is pretty much impossible to satisfy everyone with one dashboard.

When a dashboard is shared across different teams, then a specific group with special interests will start to ask more than what is in the dashboard, because their job duty is to support specific tasks within the business life cycle of the online business. In some occasions (probably most of the time), for example, when you create a web analytics dashboard for CEO, you'll always hear from some other team manager saying that that dashboard doesn't help "me" in anyway, and start to go off about what would be a great dashboard for him/her.

In a typical scenario, honest and hard working web analyst will try to make everyone happy, so he/she ends up making either an obese dashboard containing bunch of colorful charts, or bunch of redundant reports catered to every single managers in the company. You think a web site with one goal/objective would have a clear and simple dashboard for all to accept easily created, but it could get tricky. I believe it is important to think of dashboard as a starting point to dive into a pool of data.

The best way to create an effective dashboard, following points should be taken into consideration:

1. Understand the bottom line and the desired outcome of the web site.


2. Ask, why do each key business units exist in your firm and what is important for them to execute their job?


3. Know the kind of decisions your end users or business partners can make based on your dashboard.

Effective dashboards usually include:

• An intuitive graphical display that is thoughtfully laid-out, and easy to navigate.


• Logical structure so information is easy to consume.


• Regular and frequent updates of dashboard for relevance to current conditions.


• Answer fundamental questions about the web site's goal or overall business unit.


• It alerts issues or problems in such areas (error pages, ROAS, revenue, conversion rate, etc.)


• Supports decisions that impact the business or online strategies.

Killing multiple data needs with one dashboard

I am just using this phrase to push the minds to think in an effective way, so that KPIs are reported effectively to reduce redundancy. Check out this image of a scenario where you have multiple business units involved in a web site, and how they could have more data needs than that one Executive Dashboard which was created to make CEO smile and move.

The images may imply that web analyst will need to make 5 dashboards at the end of day. However, if you craft the dashboards effectively, you could potentially consolidate them to fewer reports. How you do that will depend on web analyst's skill to work with those key players and identify them KPIs for an actionable insights.

Here is a basic framework that I crafted to support approaching in creating that awesome web analytics dashboard (Tier 3 is not necessarily a dashboard, but most likely a report or an analysis.). It is intended to demonstrate that your dashboards or reports should be positioned and focused on catering the KPIs to appropriate audience/groups, and show different tiers of audiences which could reflect organizational structure with different focus on reporting needs.

Side note: If you give a web analytics access to each business units and allow one smart and motivated person to do their team's web analytics support, you can build allies of web analytics specialist. This could be a long term strategy to build web analytics culture within your company.

Data warehousing technique is growing popular nowadays. Business and corporate houses are going for data warehousing for overall business performance and productivity.

Data warehousing varies in different business set ups. Both amenities and technical hazards are associated with the practice of keeping the internal data in the online stores. It is one of the most acceptable ways of storing in-house data. Intranet is the sophisticated form of storing a company's internal records for future assessments.

Point-of- Sales records and transactions are also preserved in this mechanism. There is more than one way of online marketing data warehousing. In these systems, web analytics are maintained in online stores for easy reference.

Of the prominent ways of storing online analytics through data warehousing, we have:

• Data Mart data warehousing: Data warehousing through data marts is one design methodology. It focuses on giving up business objectives for specific departments in an organization and their development. Data marts emphasize the development of a business set up through dimension modeling locally.
• Data warehousing area wise: Web analytics data warehousing can be carried out on specific areas of particular business. Web analytic data storage starts with the data available from the online store of records. The existing records can be enriched with external data input as and when needed. Sales and purchase transaction records can be maintained through Point-of-sale data storage.
• Third Way data warehousing: In third way data warehousing, detailed business reports and needs of company set up, technical resources required for a company's progress-their availability and applications are preserved. This methodology is derived from the combination of the two major web analytic design methodology. It also states the other requirements of a business set up.

Online Marketing data stores helps us carrying out instant searches at search engines through data mining. Internal data stores offer Click-Stream data and integrated detailed click-stream data feeds. Data warehousing by Omniture help businesses prepare re-marketing lists. The web analytics also help keeping a track on the online visitor's nature, the inbound site traffic source and the online behavior of the site traffic. Data warehousing by Google Analytics and Omniture has a number of benefits to offer:

• Data Archives: Online data warehousing helps in maintaining records in archives for ready reference. Websites can keep a record of all Web traffic leading to a particular web page and the leads generated to the Website.
• Click-Stream Data on advanced search: With a simple click on the search engine, we receive click-streamed online data.
• Data warehousing leads to data feeds: With advanced search queries, the leads generate inbound links to the data. This in turn lead to valuable data feed to the website.
• Advanced segmentation of web analytics data: An advanced segmentation of the website leads to an easy availability of the relevant data. This can easily be done with the user-friendly drag and drop interface of the Google Analytics Report.
• Unique Visitor IDs: Users receive respective visitor IDs with the personalized user accounts.
• Re-marketing lists: E-commerce and Online Marketers can prepare re-marketing lists with the unique visitor IDs.
• External data integration: Most of the web analytics applications allow analyst to correlate external data by integrating it with the click-stream data. It is usually done through uploading a mapping/data file that contains a unique index key, so that data could be mashed up.

Web Browsing on Google and MSN offer user privacy mode, which enables websites to track the nature of inbound traffic to the site. There are limitations with users clearing off PC cookies on a regular basis. This leads to the removal of files and data that might prove vital for web analytic metrics.

Data warehousing for web analytics can be easily done with the help of web tools. There are web tools like Software as a Service (SaaS) that are commonly used in preparing metric reports. These tools are widely used to collect information on site operations, nature of site traffic and to make a competitive analysis of the data gathered. Number and options of website vendor support has also grown higher than before.

Data warehousing are needed to keep a track of web analytics. Figures on client data and facts on a visitor account are preserved with online data stores. Visitor accounts – its different types, sizes of the accounts and balances are well preserved. Customer-care metrics and other statistical figures are also preserved in these internal stores of records. Preparing monthly metrics to submit reports and analysis via tools like Google Analytics are also done. However, data warehousing has a number of limitations associated with it:

• Time Constraint: Preparing Reports through Online data warehousing could be time consuming if it is running through a batch process. Any re-run would cause a delay in downstream data dependencies: For this purpose, data stored on the internal database might have to be modified.
• Existing database modification: To bring in changes in the online data, the database may require modification. This in turn could raise the infrastructural cost and new software may be installed for bringing in changes.
• Threat to internal data storage security: Though the mechanism is quite effective for practical use, there might be security concerns. The database might have confidential reports with limitations. In these cases, data accessibility may have restrictions to the top management.
• Vigilance over Data warehousing: Accounting confidential reports and analyzing them with Google Analytics has its advantages. But business and corporate houses have to exercise authority on tracking the websites and modifications brought out on the internal data.

This is just a quick overview of what could be a possible pros and cons of web analytics from data warehousing stand point. It is definitely not limited to what is mentioned here in this article. This is another area of great opportunities and challenges for web analytics professionals.

Normally, the web analytics knowledge base mainly concentrates in the KPIs.

(Key Performance indicators) for e-commerce sites. It is mainly concerned with the orders, conversion rates, transactions and revenue of e-commerce sites. Non e-commerce sites are generally outlooked in the more prominent world of e-commerce websites. For all the non e-commerce website owners, here are some KPIs that are concerned with non e-commerce websites.

Before going into detail, let us consider the definition of non e-commerce websites. They are either lead generation sites or pure content sites, where visitors come for the sake of consuming content and they leave without any business transactions. It can be a technical support site, a blog, a site full of white papers, a social networking site or a brand website. Here there is a pack of contents and still there is no online outcome, which the e-commerce sites are looking for. Now, let us have a look into the major KPIs that satisfies the executive managers of non e-commerce website.

Visitor loyalty:
It is defined as the frequency of visits on your website for a specific time period. You will get the data for the average visits per visitor. For increasing the visitor loyalty for your site, set a target of a particular number of visitors that you should achieve over a specific time period and analyze the trends of your progress towards the goal set by you.

Compare your performance over period and ensure that you are making progress in achieving the predefined percentage of web traffic. It will help you know about the characteristics of your visitors. You should update your website frequently depending upon web analytics for increased web traffic.

Recency:
It is the number of repeated visits on your website. It is up to you to decide your goals regarding the recency of visitors. The greater the recency of visits, the better for your site.

If you have set the target of the recency of visits KPIs to be one day ago, it means that you want visitors to visit your site every day to enjoy the so-called valuable content on your site.

It is the normal set target for a news site or a job site. Here you will become more advantageous of the repeat visits. This will help you to know whether your site is performing well or not. If your web analytics data shows that your 67% of audience consist of new visits, then it is time to improvise upon you site content, merchandising and design. If you create incentives for repeated visitors, then sure you can enjoy success and measure your success through web analytics.

Length of visit:
It refers to the quality of visits during a reporting period depending upon how long each visit lasts. It is the most common and the most prominent KPIs used in non e-commerce sites. If by analyzing your web analytics report, you get a clear picture of the distribution of this KPI, then it is easier to proceed further. Suppose your site could increase this KPI if you make them stay on your website for one minute long, then take measures to convert more visits into a successful one by engaging your customers.

Give importance to the visitor satisfaction and they will definitely stay with you for a long period and even until eternity. Identify your own goals and measure this KPI for success.

Depth of visit:
It is mainly concerned with the number of pages consumed by your visitor in the reporting time period. It is important to note that most of the websites are now web pages and not a single page. It is more powerful than the average page views per visitor. It helps us to have a broad picture of our customer experience. Here also it helps to improve our goals and measure success.

Conversions (Site Registrations, Viewed Contact Us, Survey Participation, etc.):
Conversions may not ring the bell for those who are running non e-commerce sites, but you may have registrations page for users to receive newsletters, contact forms to contact the owner of the site, or surveys to ask your users important questions that matter to you.

These valuable actions that you may want your users to take are conversions, and it is highly recommended to tweak your analytics tools to measure these conversions and monitor its drop offs through funnels.

Thus, these are the important KPIs to be noted in a non e-commerce site. If you give importance to them then you could not only dream success but also experience it. Here are a few recommendations for the actions taken according to your web analytics data obtained

• Positively work with your goals measured against this KPIs.
• Segment the data. It will give you the key insights of how to drive the web traffic on your site. Find out the key words that drive the valuable segment of traffic to your website. Find out the most important acquisition sources for visitor loyalty and length of visit. Analyze the nature of content people with long visits consume. By this type of segmentation, you can reach your destination i.e. the measures for improvement.

All these valuable KPIs will definitely help you to increase the quality of traffic in your site and make it a better performing site with increased number of visitors who are loyal to you.

In today's highly sophisticated world, we are overwhelmed by the data flowing from all the possible sources to increase the growth rate of our business. Therefore, it is normal to expect a high output rate from our executives and thereby in our businesses by making the best use of the data amassed. Results matter most in the highly competitive world of internet marketing. However, it is not happening according to our expectations. Studies have shown that nearly 75% of the marketers does not succeed in measuring their performances making use the data provided to them.

They are also having a hard time in taking the right decision from the various reports quickly. The main reason for this hardship is their incapability to identify the key metrics that are the powerhouse of their business. As a result, they are unable to take the right measures for the quick progress. Thus, it is clear from here that unavailability of data or the right kind of data is not the main problem. The problem that underlies is the incapability to identify the most important effective metrics. In short, we are short of resources to analyze our business performance.

At such context, the significance of dashboards comes into our focus area. Dashboards are our customizable collection of report summaries. They provide us with the critical data pertaining to our business performance quickly, easily, precisely and in the best understandable form. This helps us to decide the goals for our business and take quick and the right driving measures. If you have the required skills to use your dashboards in the best possible way, then they prove out to be the greatest communication medium.

Dashboards can vary by industry and business functions. However, there are certain commonly followed best practices related to dashboards. Following this, will surely give you a better sense to deliver the key insights, and translate the performance and effectiveness of your site through dashboards. Here are the best practices...

Show the context in your dashboard:
There is no metric that can exist in isolation without the context. It will only give you a set of numbers, which will be hard for you to configure out into the related information. If you place your metrics in the contexts then it will definitely give you quick insights rather than a bunch of questions regarding the data. It is easy to show contexts in your dashboard. You can use internal and external benchmarks, goals and prior performance as a context. Without the context, your metrics will not give you the sort out value even if it is the most critical metric for your business. The purpose of the goal in your dashboard is to communicate the performance and to improvise your actions for the required results. Segmentation is the most effective way to access key insights regarding your good or bad performance.

Pick out the critical few metrics:
You may be aware of the fact that dashboards are not merely one page, but 28 tab excel files or 34 slide PowerPoint decks. As a result, these track all of the metrics regardless of their relevance. It makes more difficult to have the accurate understanding of the significant points and makes us in a confused state relating to the required actions. You should have a brainstorming session to grasp the few key metrics significant for your business. If you succeed in figuring out this difficult issue, then it will really give your dashboard the perfect decision making power.

The rule for selecting the key metrics is that they should be less than 10. If they are greater, then it will be less effective. You should identify a goal for each of these selected few, segment it, and display the goals and metrics in your dashboard.

Take special efforts to include insights in your dashboard:
In the absence of a set of insights that make you available with performance information and the driving action, your dashboard will merely turn into a set of graphs, numbers and statistics. These insight freer dashboards leave everything to the intelligence and capability of the reader. If you provide insights, then it will illuminate the thought process of the reader quickly to take the right action.

So include a session in the top of the dashboard to highlight your insights. The insights may range from the reasons for the hits and misses, the underlying causes for the shifts in the business and the root causes. The recommendations you share on the dashboard can be relating to our next action, the new merging horizon of opportunity, or the method to reverse the decline. This will increase your senior executive's skill to take the right decision without having to go through all the unattractive statistics.

Single page for your dashboards give you the best results:
You should realize the power of the single page dashboard. If your dashboard is not single page, then it is not a dashboard but a report. Single page is the best practice since it is packed up with advantages. It helps to make dashboards present the data in the neatest manner with only the required data and not an overflow of data. It makes data presentation easier, enhances the understandability of it, and of course, makes it portable. It also promotes much hard work in choosing the few critical metrics.

Constantly evolve and stay relevant:
Dashboards should not be made into a permanent outdated thing. In this world of change, help in the evolution of your dashboards. Metrics should be eliminated as soon as it loses its relevance. As the web changes at least a few of your key metrics will change according with it. So plan the evolution of your dashboard. Otherwise, your dashboard will consume your enormous time without giving you the perfect value.

All these actions will definitely make a positive output to your business and audience.

A Key Performance Indicator (KPI) is a visual cue that communicates the amount of progress made toward a goal.

First you need to ask yourself:
- What drives the success of your website?
- To whom are you addressing the success (it is possible that there are several stakeholders?

KPIs are quantitative measurements that help an organization measure progress towards goals and identify areas of improvement.

KPIs should be "Actionable". Consider data that are "good to know" as other metrics supportive to KPIs.

Websites along with multiple campaigns promoting different objectives could be complicating to certain stakeholders. Such reporting could be broken out by projects or wrap reports, addressing its own KPIs for campaign specific objectives.

Website KPIs and reporting can associate to these individual marketing efforts, and address the success of the website.

Recently, Wall Street ignored comScore's disclaimer on the limitations of its metrics data, causing people to expect lower Google's revenue. It turned out that Google had stronger earnings for the first quarter of 2008. Here is the article from NY Times "Web Metrics and Grains of Salt". Web metrics data could be much helpful if more questions.

The learning from this incident from web analytics strand point, never settle with one main data point and question beyond the given metrics. In this incident, it would be comScore reports showing a slowdown in paid clicks on Google's sites. If you're a web analyst, it is important to ask yourself beyond what is given.

I highly doubt those Wall Street analysts only gauged on that one specific data, but when it comes down to analyzing web metrics, there would be far more questions arising out of these data. (I'll limit it to few key questions since the list can go on forever)

• In this specific scenario, is comScore limiting "paid clicks" to just Google's SERPs (search engine result pages)? Google's content targeting ads are placed on so many other websites, and that should automatically tell us that Google's revenue aren't just limited to their domain.

• comScore's projection was based on United States market, how much of that would be accounted in Google's revenue?

• Do increase/decrease in clicks automatically associate to higher or lower revenue? I don't think so, if Google says quality of clicks will be enhanced, there is a possibility that each clicks could weigh more in terms of money. In another word, enhancing for qualified click-throughs mean higher conversion, and potentially allowing Google to generate more money (in areas of referrals, high value keywords, competitive keywords, etc.)

• Traffic from other countries beside United States probably offset slower growth, but if you're not sure what Google's revenue drivers are then, how can you assure lower revenue from such company?

Although I'm talking about Google in general in this case, the kind of thinking process to ask beyond a data point to generate next questions is an important process in web analytics. So this article by NY Times, states at the beginning "Perhaps Internet metrics should come with a warning label: "handle with care." is actually not a bad idea. Web analytics are great to analyze "what" is going on with the site, but it always has been a challenge to compare it across different software platforms, different medium, etc.

So when using web metrics to associate data across different platforms or environment, it would probably wiser to count on web analytics specialist rather than wall street analyst, because web metrics data needs to be handled with care.

One of the biggest challenge in reporting the project results (promotions, campaigns, media buys, etc.) is reporting the metrics that come from multiple analytics systems.

As a web analytics analyst, we would make sure to track and tag any source that we could identify as a campaign. However, when we have the opportunity to track things from mulitiple system, the challenges in reporting arraises during the time to report the results to the business.

Every analytics system tracks and processes the data differently, and we all know that analytics tools are not accurate. Analysts would rather rely on the precision rather than accuracy. Making sure that we understand these issues accuracy, we have to rely on viewing the data from the system that we know what the data should mean.

One of the example situation when we have to rely on multiple analytics platform is when ads are served via third party ad serving platform (DoubleClick, Atlas, EyeWonder, Google AdWords, etc.). Additionally, most likely the site analytics tools are utilized to track the instances or responses from those ads. The question arrises during the reporting, which data should we use, ad serving platform or site analytics tools?

The answer is both. In terms of the ads' impressions, interaction, clicks, and click-throughs, it is better to use those metrics from those ad serving platforms. The click-throughs usually never match with the instances or responses seen in the site analytics tools. What we would like to use from site analytics tools are the traffic behavior and additional insights available from the tools.

Here are some possible breakdowns in the reports when multiple systems are used:
(Let's say in this scenario, we are using DoubleClick and HitBox)

Ads impressions - DoubleClick
Clics - DoubleClick
Click-through rate - DoubleClick
Interaction rate - DoubleClick
Conversions/Retensions - Possible to use DoubleClck's spotlight tags or HitBox
Avg. Time on Site/Page - HitBox
Traffic Segmentation - HitBox
Traffic Behavior - HitBox
Visitors to the site via the ads - HitBox

A lot of marketers and business managers deal with a lot of the website KPIs as more businesses are investing more money into online.

Important concept that people would have to understand is the differences in the common metrics and KPIs used in the site analytics industry. Following KPIs are examples defined in web analytics association's document.

These basic terminologies would be the best starting point to understand and generate KPIs that are actionable to your website business strategies.

KPI Definition Framework

• Count: Basic unit of measure, not a ratio. Ex) Visits, Page Views, Total Sales


• Ratio: Typically, a count divided by a count. Ex) Page Views per Visit


• KPI (Key Performance Indicator): KPI can be either a count or ratio, it is infused with business strategy, the set of appropriate KPIs typically differs between site and process types.


• Dimension: A general source of data that can be used to define various types of segments or counts and represents a fundamental dimension of visitor behavior or site dynamics.

Metrics can be applied to three different universes:
Aggregate, Segmented, Individual

Building Block Terms

Page:
Type - Dimension
Universe - Aggregate, Segmented, Individual
A page is an analyst definable unit of content.

Page Views
Type - Count
Universe - Aggregate, Segmented
The number of times a page was viewed.

Visits (Sessions)
Type - Count
Universe: Aggregate, Segmented
A visit is an interaction, by an individual, with a website consisting of one or more requests for an analyst-definable unit of content. If an individual has not taken another action on the site within a specified time period (typically, 25 to 30 min), the visit session will terminate.

Unique Visitors (New Visitor, Repeat Visitor, Return Visitor)
Type - Count
Universe - Aggregate, Segmented
The number of inferred individual people, within a designated reporting timeframe, with activity consisting of one or more visits to a site. Each individual is counted only once in the unique visitor measure for the reporting period.

Visit Characterization

Entry Page: Type - Dimension
Landing Page: Type - Dimension
Exit Page: Type - Dimension
Visit Duration: Type - Count
Referrer (Internal, External, Search, Visit, Original): Type - Dimension
Click-through: Type - Count
Click-through Rate: Type - Ratio
Page Views per Visit: Type - Ratio

Content Characterization

Page Exit Ratio: Type - Ratio
Single Page Visits: Type - Count
Single Page View Visits (Bounces): Type - Count
Bounce Rate: Type - Ratio

Conversion Metrics

Event: Type - Dimension
Conversion: Type - Dimension

If you are interested in how to utilize the web metrics/KPIs for analysis, check out the site traffic analysis section.

Source: http://www.webanalyticsassociation.org

As a web analyst, sometime during the project, you would deliver a web analytics/metrics report with necessary key metrics to your counter parties (clients). Apart from the technical part of the report, it is most important to deliver what clients want and expect to deliver metrics that are actionable to their business. I have heard of a case where client thought the report was auto genera

So what do web analysts need to do to make them special in terms of reporting?

Regardless who you are reporting the metrics to, web metrics need to be reported in certain format or forms. Some users might prefer PDF files; excel sheet, word documents, extranet web reporting, business object, crystal report, etc.

Every company has there own standard of reporting practice, and web metrics would most likely need to comply with such reporting practice done by your clients. Due to security issues, certain clients would want the reports to be published in their secured extranet environment in web based format. Some clients would probably want to receive the web metrics in a form of excel sheet, so their in-house analyst can process the data in their own method.

Reporting the web metrics data to your end users is an important task in web analytics. Not everyone will have the access to the web analytics software and be able create customized dashboards. When considering the counter party�fs role, you should be able to tailor the web metrics data to fit their interest.

Some of the users that the metrics data will be delivered to would be:

Each role would have different interests in the kinds of metrics data that they would appreciate. For example, executives would care more about top-line traffic data, and care less about the internet browsers types and versions used by visitors.

When considering reporting the metrics data, you might want to consider how your users would want to receive the report. Some of the formats to consider are PDF, word documents, excel sheet, xml data, extranet web dashboard, etc. Best practice is to understand what and how your users or clients want out of the web analytics data since every one of them can be catered in different ways.