Rajesh wanted to purchase a new ayurvedic toothpaste. He goes to Amazon.com and then using its search engine looks for toothpaste and specifically for ayurvedic toothpaste. He selects five to six brands such as Patanjali, Herbal, Colgate, Ayush, Himalaya, etc. For each brand he would read its review, look at its pricing, product specification and the size at which it is available. After going through these brands, he decides to purchase Ayush ayurvedic toothpaste.
Now this entire consumer lifecycle of Rajesh from his need stage (New ayurvedic toothpaste) to the purchase stage (bought Ayush toothpaste) is the purchase funnel. At the need stage there will be hundreds of brands present in the market. Then at the behaviour stage he would go to amazon.com where there might be some 20 ayurvedic toothpaste brands. After looking at the popularity indicator he would select some five to six brands. After going through their reviews, pricing, size, specification he would finally purchase one toothpaste. At each level from need stage to the conversion stage there is a drop of products or brands by user. Some brands are preferred more than the other and finally one is selected.
In the similar scenario, Rajesh would go to the local fish market to purchase fish. He would look at the type of fish he likes, what is the price, how is their quality, what is their weight, etc and depending on each specification he might not purchase some fish over the other. Now even this lifecycle of purchase from the need stage to the conversion stage is the purchase funnel. Rajesh keeps on filtering the fishes he wants to purchase depending on certain criteria and finally makes a purchase of the fishes which meets his criteria.
Digital Analytics comes into picture here. Using Digital Analytics, amazon.com could measure users like Rajesh and try to figure out what is working for the consumers, what is that the consumer likes, how is he navigating through the different pages and how much is his engagement level at each level which can’t happen in an offline world.
A Basic Purchase Funnel Will Have The Below Stages:
- Acquisition involves building awareness and acquiring user interest for your product or service.
- Behaviour is when users engage with your business.
- Conversion is when a user makes a purchase and becomes your customer.
Generally, in the brick and mortar world, It becomes very difficult to understand at what stage a user drops out as the data is not commonly available to analyze. However, the explosion of connected smartphones, tablets, and desktop computers has made the individual web user more connected than ever, enabling marketers to monitor and collect engagement at every touchpoint in the purchase funnel using digital analytics. We can exactly track the lifecycle of a consumer. With the advent of technology such as cloud computing and modern computing power, the data is connected more seamlessly than ever before. This data can help us to make better and informed decisions as to what is and what is not working for the users, thereby acquiring newer users and increasing our conversion rate. In short, Digital Analytics is the collection, measurement, analysis,
Application Of Digital Analytics
We can consider a clothing company who has a range of products. Now, the company wants to venture into online space for selling their fashion labels. They might start with multiple categories and have a look at the various trends using digital analytics.
Digital analytics can help them to get answers to some strategic questions which can help them to analyze their marketing strategies.
Some Of The Questions Which Digital Analytics Platform Can Answer Are:
- From which location is the maximum number of orders coming?
- What is the page which has the maximum dropouts?
- Which page has the highest engagement?
- Are we getting repeat customers?
- Which device has the higher user engagement? Etc etc
By trying to analyze specific questions, targeted marketing strategies can be implemented. For example, when the company knows that a certain location has a huge order base it can mean that the product is trending in that area. Higher marketing spent can be done there in order to increase the visibility for the brand, maybe even start an offline store to tap those who are not purchasing online.
The Basic Lifecycle In Digital Analytics Consists Of Four Steps:
- Measure – Collecting data to analyze from all the possible platforms
- Analyse – Try to make sense of data. Find interesting patterns, insights, and anything different in the data. In order to analyze the data, it is imperative to have a good understanding of the business objectives by collaborating with different teams in the organization. This will help us to find insights into the right questions. For example, which social media platform works the best? Which location has the highest sales figures? What product is the best seller? Etc.
- Report – Since the analytics team collaborates with different teams across the organization. It is important that the data should be reported in a manner which is clear, simple and actionable for everyone in the audience.
- Test – Based on the insights, different strategies can be planned. Test phase will help us understand and implement the best strategy for the business.
This being a cycle will be repeated again. The campaign will again be measured, analyzed, reported based on which new strategies will be planned to be tested and so on.
A Simple Example Of Digital Analytics Cycle Would Be Of A Bag Sale On Your E-Store
- Measure: After Implementing a strategy to sell three models of bags out of the ten launched. The first and the basic step would be to measure the number of individual sales number for different bags.
- Analyse – Now we would like to know which model has the highest number of sales. Along with that the different location from where the orders are coming, the device platform for where the sales
takesplace, what and how is the engagement level of a user before making the final purchase, etc
- Report – After finding answers to these questions. It will be reported to the marketing, communication, sales team in order to formulate a new marketing strategy for the outcome
fromthe previous campaign
- Test – These new campaigns will be tested to find out the most effective ones and if required any changes that
needsto be done for them.
However, When Using Digital Analytics As A Part Of Our Company Culture, Care Should Be Taken On The Following Points:
- Are we analyzing the data keeping the context in mind?
- Are we trying to find patterns to fit our story or do we try to make real sense behind these patterns?
- Are we answering the 5 Whys – Who? When? What? Why? And How? With respect to our objectives
- Though the questions will be measured, analyzed and reported. It is not a Pandora’s box. It will always take collaborations with different teams to come up with an actionable plan to get our desired output. Like how a doctor will diagnose the patient by asking him about various symptoms or maybe even ask him to take some test before concluding. The test in itself will not tell what is wrong with the patient. It is the combined efforts of the lab results and the doctor’s expertise which will help him conclude.
The Various Businesses Where Digital Analytics Can Be Applied Are:
- Publishers can use it to create a loyal, highly-engaged audience and to better align on-site advertising with user interests.
- Ecommerce businesses can track the customer purchase lifecycle and use it to better market their products or services.
- Lead generation sites can collect user information for sales teams to connect with potential leads.
- Online information or support portals can use to it to understand the ease of finding information such the time spent on the site, bounce rates, exit rates, etc.
- Branding can be measured by brand penetration, engagement and loyalty. How many people follow, comment and share on social media, etc.
Digital Analytics Can Be Measured By Collecting Data From Various Channels Such As:
- Mobile applications
- Online point-of-sales systems
- Video games consoles
- Customer relationship management (CRM) systems
- Social media
- Email marketing
Sometime it becomes very challenging to collate the data from multiple sources such as social media, web analytics, email marketing tool, etc it becomes slightly difficult to answer our business questions seamlessly. In order to solve this problem, it is always wise for brands to invest in a platform which will bring all these channels together. Though these will be cost associated to this the returns will outperform the cost if it is used to improve and optimise the marketing strategies for the business resulting in better outcomes.
The data from multiple sources can be compiled into Analytics reports, which can be used to analyze and understand customers and make effective marketing strategies. With the world going digital, it will just keep on going to become a big part of every marketing team.