Certainly, pitching leads is an ultimate motto. But today, it has come across just pitching. When Google launched Adwords in October, 2000 with 350 customers, it might have foreseen its extraordinary scalability. Within the next two years, the internet users’ count surpassed 558 million across the globe. Upon measuring its popularity, the leading social network, i.e. Facebook, opened itself as an advertising platform on 22 August, 2006. Adsense has proven another milestone, as it was rolled out to target the mobile audience in September, 2007. If you talk about its vulnerability at that time, China Internet Network Information Center (CNNIC) report showed that only 50.4 million or just 24% users were accessing the mobile internet.
Gradually, Facebook and other big shots of the internet marketing domain sensed the power of demographics analysis. It determines the statistical data relating to the population and particular groups within it. There upon, the analytics of online ads together with website traffic started proving a value, rather than being a noise.
Online Customer Journey:
Today, it provides with prospects worth million dollars. You can take data analytics as a pool of opportunities as it hides opulent data about customers. The veteran data analysts sail through many challenges while mapping, building and optimizing digital customer experience. They prove potholes, making their browsing a bumpy road over the internet.
Digital marketers together with analysts smoothen by integrating innovations. During online browsing, the idea of exploring information makes a round at the back of the user’s mind. The intelligence driven from his ad experience evolves blockbuster ideas.
To understand ‘how’, let’s get through the stages of the online customer journey, which builds digital customer experience.
Search: The customer begins online journey as a searcher. As you type, for example, in the Google online Nike sport shoes for men. The SERPs will pop up ads with ten top ranking results. Later on, it takes him toward the path of the online transaction.
Discover: This stage narrows the search to the ad of products or services that has a potential to be used. If the user clicks any discovery or gallery ad, for example, the products show the matter of his interest.Those potential requirements are termed as a use case.
Think of: Subsequent to discovering range, hethinks about its potential. His rummaging eyes search for desirable features and price range. As he gets, he continues to engage with that product for more minutes. It shows the fire of enthusiasm clicks the list of most intended products/services.
Decision making: It is a crucial part of his digital experience, as his decision brings him to the verve of making a deal. Therefore, he adds the items/ services to the cart that he intends to be carried out.
Sign Up: This stage sets the ground to complete the transaction. It authenticates who the user is.
Personalise: This phase mirrors whether or not the user intends to configure personalised experience. As he completes the transaction, the delivery on requirement embeds a personal experience.
Action: It defines the usage. To better determine his actions, the analytical report taps on the feedback or customer reviews.
Engagement: The data analysis of his usage peaks, monitoring activities, time spent on per activity, and willingness to refer to professional or personal network defines the engagement.
Abandon: Sometimes, the user switches to another search. He abandons exploring at a certain point. That point is significant to assume the reason for abandoning that journey. Thereby, it provides with many cues to re-target with optimized sales.
Exit: It is the end stop whereon the user stops using the product/service.
These stages hide critical information about navigating the sales funnels. The blockbuster ideas of how to unlock more transactions and higher usage lie here. Moreover, that analytical report supports in integrating products and services to sail, act, engage and behave surrounding that products/ services. It further underscores the processes to analyze the data. Thereby, building the process to classify and detect where the user is in the pan journey.
In the nutshell, the predictive analysis requires figuring out information of every online visitor at each stage. This analysis, at the end, feeds the intelligence to configure future ad campaigns, form of data, channel and content marketing techniques. Simply say, the analysis of data avails users experience at each stage of the transactional journey.
What is information analytics?
The set of data translates into information through data mining. It assists in pulling insights from the data that reveal the whole online experience by the end user. That insight seeds patterns to convert intention into sales. In other words, information analytics deals with deriving value from the set of variant datasets.
What values does information analytics configure?
1. Data regarding maximum sales: This information is built around the datasets that point at maximizing value to the business. Certain databases evaluate such information that the end users lookup for making decision. The entrepreneurs use it to consistently drive value to their business.
2. Segmentation of customers: Those end users who maximize sales should be separately identified to drive the most business transactions. It empowers the entrepreneurs to dispatch the information to those users for fulfilling specific needs. From the lens of the business, this information can be utilized to cater price and packages for maximizing revenue & business value.
How should information analytics-driven intelligence be delivered?
Data mining and analyzing dig key performance indicators (KPIs). If the entrepreneurs fail to identify, and track, users’ engagement and retention will be a Herculean task. Also, the KPIs should augment the product experience with accurate and contextual information timely. Otherwise, they leave users disappointed, disengaged and disoriented.
The KPIs underscores information that assists in spinning information, channel and stages around the values to the business. That knowledge should be combined and distribute to all users who are segmented under the same group. At the end, it draws similar value from that user base.
The mining of user experience pulls out users’ pattern. Thereby, building a comprehensive map of various touch points according to their purchase funnel is like a walkover. The entrepreneurs should also build that experience around appropriate channel. It is optimally built and actively managed, the information capturing gets double. The correlated users frequently start engaging with.
The more users learn, the more you earn. If you end up catering contextual information to the right users, the difference will start emerging in sales and transactions.