Thursday, January 1, 2015

Getting started with digital analytic

digital analytic,Google Analytics,Google Analytics tracking,

·       The importance of digital analytic

Digital analytics is the analysis of qualitative and quantitative data from your business and the competition to drive a continual improvement of the online experience that your customers and potential customers have which translates to your desired outcomes (both online and offline).
One of the most important steps of digital analytics is determining what your ultimate business objectives or outcomes are and how you expect to measure those outcomes. In the online world, there are five common business objectives:
·         For ecommerce sites, an obvious objective is selling products or services.
·         For lead generation sites, the goal is to collect user information for sales teams to connect with potential leads.
·         For content publishers, the goal is to encourage engagement and frequent visitation.
·         For online informational or support sites, helping users find the information they need at the right time is of primary importance.
·         For branding, the main objective is to drive awareness, engagement and loyalty.
There are key actions on any website or mobile application that tie back to a business’ objectives. The actions can indicate an objective, like a purchase on an eCommerce site, has been fully met. These are “macro” conversions. Some of the actions on a site might also be behavioral indicators that a customer hasn’t fully reached your main objectives but is coming closer, like, in the eCommerce example, signing up to receive an email coupon or a new product notification. These are “micro” conversions. It’s important to measure both micro and macro conversions so that you are equipped with more behavioral data to understand what experiences help drive the right outcomes for your site.

·       Core analysis techniques

Segmentation allows you to isolate and analyze subsets of your data. For example, you might segment your data by marketing channel so that you can see which channel is responsible for an increase in purchases. Drilling down to look at segments of your data helps you understand what caused a change to your aggregated data.
Examples:
·         You can segment your data by date and time, to compare how users who visit your site on certain days of the week or certain hours of the day behave differently.
·         You can segment your data by device to compare user performance on desktops, tablets and mobile phones.
·         You can segment by marketing channel to compare the difference in performance for various marketing activities.
·         You can segment by geography to determine which countries, regions or cities perform the best.
·         And you can segment by customer characteristics, like repeat customers vs. first-time customers, to help you understand what drives users to become loyal customers.

·         Conversions and conversion attribution

1.     A macro conversion occurs when someone completes an action that’s important to your business. For an ecommerce business, the most important macro conversion is usually a transaction. A micro conversion is also an important action, but it does not immediately contribute to your bottom line. It’s usually an indicator that a user is moving towards a macro conversion. It’s important to measure micro conversions because it helps you better understand where people are in on the journey to conversion.
2.     Attribution is assigning credit for a conversion. In last-click attribution, all of the value associated with the conversion is assigned to the last marketing activity that generated the revenue. However, there are other attribution models that can help you better understand the value of each of your channels. For example, rather than assign all of the value to the last channel, you might want to assign all of the value to the first channel, the one that started the user on the customer journey. This is called first-click attribution. Or, you might assign a little bit of value to each of the assisting channels in the customer journey.

·         Creating a measurement plan

The measurement planning cycle consists of the following:

·         Define your measurement plan.

 

1.      Document your business objectives.
2.      Identify the strategies and tactics to support the objectives.
3.      Choose the metrics that will be the key performance indicators.
4.      Decide how you’ll need to segment your data.
5.      Choose what your targets will be for your key performance indicators.

·         Create an implementation plan.

After defining your business needs and documenting the technical environment of your business, create an implementation plan that is specific to the analytics tool that you’re using. For Google Analytics, this means defining the code snippets and specific product features that you’ll need in order to track the data defined in your measurement plan. 

·         Implement your plan.

The next step is to have the web development team, or the mobile team, actually implement the tracking recommendations that you’ve made. Some website technologies will require additional planning, such as:
o    Query string parameters
o    Server redirects
o    Flash and AJAX events
o    Multiple domains and subdomains
o    Responsive web design

The most common features used in a Google Analytics implementation plan for a website:

 

o    Implement the standard Google Analytics tracking snippet. This gives you the bulk of the data you need.
o    Determine how to track your KPIs. You can do this using goal tracking and the eCommerce module if you are an ecommerce business.
o    Use filters to normalize your data so that your reports are accurate and useful.
o    Use campaign tracking and Ad Words linking to properly track marketing campaigns.
o    Use custom dashboards and custom reports to simplify the reporting process.

        Maintain and refine.

The final step of the measurement planning cycle is to maintain and refine your plan. Your business requirements and your technical environment can change over time. Without a team to maintain your measurement plan, your data won’t keep pace with your reporting needs.