Website Analytics

Our proprietary web analytics tools assess website effectiveness and assist in business and market research. The primary function of our tools is to measure, collect, analyse and report a website’s data for understanding and optimizing its usage. We extend this by using our analytics applications to measure the results of traditional print or broadcast advertising campaigns. Through this we can assess how traffic to a website changes after the launch of a new advertising campaign, outreach or a promotion.

We use a four-step process for analysing website data. The first step involves continuous collection of website visits and clicks. The next step involves turning this data into ratios and metrics. We then overlay a key performance indicator (KPI) framework on the data. This stage focuses on using the ratios (and counts) and infusing them with business strategies. We use the KPIs in formulation or modification of online strategies.

Our KPIs and associated analytics includes drivers and conversions, e.g. the degree to which different landing pages are associated with online purchases. We typically use this data to compare against key performance indicators for performance, and use it to recommend improvements in a website or marketing campaign’s audience response. We use Google and Adobe Analytics tools and supplement these with other services that provide additional layers of information, including heat maps and session replay.

Our data collection methods include server log file analysis and page tagging that uses JavaScript embedded in the webpage to make image requests to a third-party analytics-dedicated server, whenever a webpage is rendered by a web browser or, if desired, when a click occurs. As applicable we use both mechanisms to collect data.

Our direct HTTP request data comes directly comes from HTTP request messages (HTTP request headers). We also use network level and server generated data associated with HTTP requests e.g. IP address of a requester. Application level data sent with HTTP requests is generated and processed by application level programs (such as JavaScript, PHP, and ASP.Net), including session and referrals. These are usually captured by internal logs rather than public web analytics services.

We combine external data with on-site data to help augment the website behaviour data described above and interpret web usage. For example, IP addresses are usually associated with Geographic regions and internet service providers, e-mail open and click-through rates, direct mail campaign data, sales and lead history, or other data types as needed.