Web Analytics and Reliance on Data

            Web analytics is gathering web and app data and performing analysis and reporting on it to make design, marketing, optimization, or other business decisions.  From web data, companies can determine customer behavior in their apps and websites, purchasing behavior, social network behavior, and identify what content or products are getting attention from which demographics.  Web analytics enables companies to set informed goals, gain visibility on events and metrics related to them, and gain visibility on key performance indicators (KPI) to measure their progress toward those goals.  Web analytics helps companies increase customer retention and conversion by designing their sites, apps, ads, and social content around the analytics.  Web analytics can power marketing and remarketing campaigns to increase revenue by focusing on the right users with the right content.

Goals:

            Goals are specific desired results that reflect business objectives and strategies (Kaushik, 2010).  Ideally, goals are SMART, meaning that they are specific, measurable, attainable, relevant, and time-bound (Mind Tools, n.d.).  Goals are used to support and guide a company, team, or individual toward achieving business objectives, and are fed by the company’s mission, vision, and strategy.

            In the realm of web analytics, goals are the specific results that must be achieved by the website or online store.  For instance, if the business objective is to increase sales revenue by 10% in a year.  An example of a goal to support this business objective might be to generate 25% more visitor traffic to the website through affiliate campaigns, email campaigns, pay-per-click ads, and remarketing.  Another example of a goal to support this objective is to increase customer sales by reducing shopping cart abandonment by 5% and streamlining the checkout process to cut checkout time by 50%.

Events:

            Events are the steps in the process of achieving a goal (N.A., 2012).  Events are the steps a user takes when navigating a website, between initial visit and checking out.  On a website, a goal might be making a sale.  The events to accomplish that goal are the searches, navigation, product selection, verifying the product is in stock, checking the reviews, adding the product to the shopping cart, shipping selection, checkout, and confirmation.  Other examples of events could be the events in processing a return.  The customer might go to the site, go to their order history, and click ‘return’ next to the item that they want to return, followed by asking for a reason for the return, and producing a shipping label for the customer.

            Relating to web analytics, metrics can be gathered for each of these steps in order to tune the user experience.  Events, in a process to achieve a goal, can be analyzed in a funnel analysis (N.A., 2012).  Like in a value stream map or a process analysis, data for the time the customer spends in each step can be recorded and analyzed, as well as the most common paths to the goal.  The business can then use that data to improve the efficiency of the website or app achieving that goal.

Key Performance Indicators (KPI):

            Key performance indicators (KPI) are quantifiable measure of performance for an activity or goal that is important to a business (Nunneley, 2019).  In other words, a KPI is a number that measures some important piece of information that is important for measuring progress toward some target goal (Kutz, 2016, p.175).  A company or department will usually define key performance indicators around activities that are important to achieving the company or department goals.  These indicators serve as a part of the control cycle of management (Kutz, 2016, p.178) and show how close the performance is to the target values as well as reporting and monitoring metrics.

            Relating to web analytics, key performance indicators are the key targets for websites, online marketing, and online stores.  They may measure how many visitors came to a landing page as a result of a click from some online ad, for example.  Another example of a KPI in web analytics is the ratio of visitors to people that actually made a purchase.  Other examples of KPIs are geographic source of visitor traffic, number or amount of sales, or how many visitors with items in their carts left the site before checking out.

            In another example, if the goal is to generate 25% more visitor traffic to the website through affiliate campaigns, email campaigns, pay-per-click ads, and remarketing, then a supporting KPI might be the number of visitors to the site.  Other important supporting metrics would be the number of visitors from affiliate ads, number of visitors from email campaigns, number of visitors from pay-per-click ads, and number of visitors from target remarketing.

Goals, Events, and KPIs:

            To illustrate the difference between these ideas, picture a goal for a web app.  That goal might be to increase the conversion rate (the amount of users that buy something) to 70% (N.A., 2012).  The events are the steps leading up to a purchase that the user takes.  Key performance indicators (KPI) would be the actual conversion rate, like 36%.

Google Analytics

            Google Analytics is an analytics platform developed for web traffic and marketing analytics.  Companies use Google Analytics to track page performance, ad performance, performance of certain content, flow through pages, and bounce rate (amount of visitors navigating away from a site after only visiting one page) (Forbes, 2017).  Google Analytics is being used to judge the performance of not only websites, but apps, and any other web-available content.  It is consumable by anybody with a website and any size of company.

            Google Analytics can be added to any page by adding a JavaScript code snippet to the page.  That little snippet of code pulls in Google’s ability to track all of the traffic related to that page, the demographics of the visitors, their geographic location, the devices and browsers that they use, what keywords or search terms bought them to the site, what actions users take on the site, which users fill out contact information, which users from which demographics view which content or make purchases (Leadem, 2018).

            Companies can use this analytic data to make redesign decisions, content changes, or inform marketing to make ad changes or change target demographics.  It can also be used to identify problems regarding mobile or tablet usage.  Handy and commonly used features include seeing how much traffic is channeled in from social media, determining the return visitor rate, and finding out where shoppers abandon the order process.  Businesses can create goals in Google Analytics and use those goals to track conversions (Leadem, 2018).

            Google Analytics is also used to create revenue and inform the marketing strategy by honing in ads, pay-per-click (PPC), and remarketing campaigns on repeat visitors, people who abandon their carts, people who invest time researching and going through the funnel but navigate away, and certain demographics of users who are drawn to the content relating to profit-generating products and services.  Google Analytics can be used to identify which social networks to purchase ads through because it tracks what traffic is coming from which networks.

The Future of Web Analytics

            In the future, web analytics will continue to be more comprehensive and pull in data from other sources in the big data movement to form relationships between users, social networks, sites, purchase history, and preferences, allowing a one-to-one marketing capability for websites and apps that are leveraging that data.  Sites like Amazon use purchasing data to show customers items that appeal to them or use purchase data to show customers what items they should purchase with an item based on what other customers purchased.  Google sculpts search results and shopping results based on the user’s preferences based on analytics and data.  Companies with analytics capabilities are using their data to make more sales by positioning the product that the customer wants in front of them at the exact time that they want it.  Both Google and Facebook are notorious for “listening” to a customer’s wants.  If a person searches for something you are interested in purchasing on Google, there is a good chance that they will see multiple ads or references to that item soon afterwards.

            Web analytics meeting big data will continue to be commoditized and become more accessible to sites and companies that may not have that historical data, but are willing to pay for it, enabling analytics to drive automation on websites and applications.  A user will open a new site or app and be presented with content and products that are already chosen for them based on big data and web analytics piecing together a user’s behavior before they have ever been to a site.  There are several companies, such as SAS, that have created analytics platforms that allow businesses to leverage web analytics, big data, and artificial intelligence.  Companies like this will continue to appear and the service will become more accessible and commoditized.

            In conclusion, web analytics is creating opportunities for business growth, increased customer service and retention, increased sales and revenues, better marketing and more targeted content and ads.  Web analytics allows companies to make goals, monitor events, and control their decisions using key performance indicators (KPIs).  Google Analytics has made web analytics accessible to companies of any size.  Web analytics platforms like SAS or others are opening up capabilities for companies to use web analytics to make automation decisions to improve web traffic using web analytics alongside big data and artificial intelligence.

References

Forbes Agency Council. (2017). 14 Ways You Can Use Google Analytics to Improve Your Website.

Kaushik, Avinash. (2010). Occam’s Razor. Retrieved from https://www.kaushik.net/avinash/web-analytics-101-definitions-goals-metrics-kpis-dimensions-targets/

Kutz, M. (2016). Introduction to Electronic Commerce: Combining Business and Information Technology. Bookboon.com

Leadem, Rose. (2018). A Small-Business Guide to Google Analytics.  Retrieved from https://www.entrepreneur.com/article/314343

Mind Tools. (n.d.). Personal Goal Setting: Planning to Live Your Life Your Way. Retrieved from https://www.mindtools.com/page6.html

N.A. (2012). eMarketing: Online Marketing Essentials. Licensed under a Creative Commons by-nc-sa 3.0 license. Retrieved from: https://open.umn.edu/opentextbooks/BookDetail.aspx?bookId=1

Nunneley, Laura. (2019). What is a key performance indicator (KPI)? Retrieved from https://www.geckoboard.com/blog/what-is-a-key-performance-indicator-kpi/

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