1990s marked the birth of Customer Relationship Management (CRM) systems in true sense. Giants like Oracle, newcomers like Siebel Systems and innovators like Salesforce towards the dawn of the century gave birth to the most advanced and widely used concept in the world of marketing – Customer Relationship Management. Though the concept of collecting customer data, analyzing it to customize communication with customer was present much before the term CRM was coined, the modern-day CRM solutions go much beyond the traditional task of collecting and analyzing data. In the past four decades, CRM solutions have come a long way where it has given birth to a new concept, Visitor Relationship Management – Visitor Relationship Management, to provide justice to the new and still evolving online business models.
According to Statista, the worldwide retail e-commerce sales in 2016 was USD 1.86 trillion and is expected to reach USD 4.5 trillion by 2021. In 2016, an estimated 19 percent of all retail sales in China occurred via internet; while, the same percentage in Japan was 6.7 percent. According to a December 2016 study by Pew Research Center, eight in ten Americans were shopping online; around 79 percent consumers shop online in America, up from just 22 percent in 2000. There has been a significant increase in the number of people and frequency at which they are shopping online. As it is said that the bigger the market, fiercer is the competition; same has been the case with online industry. With this spurge in growth and fiercer competition, it becomes more and more imperative to understand customers, their needs, their requirements, their interests, and much more about customers.
Why businesses need Visitor Relationship Management
In the recent times with rising competition and decreasing margins, the onus on marketing teams has been increasing to target more and more customers with increased conversion rates and reduced marketing budgets. In such a scenario, it becomes imperative to come up with frameworks and models to target the right customers, through right channels and at the right time with right choice of products and services. Visitor Relationship Management is a solution which can help us achieve this. What Customer Relationship Management or CRM is to the offline lifecycle of a customer, Visitor Relationship Management or Visitor Relationship Management is to the online lifecycle of a customer. Visitor Relationship Management solution has similar objectives as the CRM solution – gathering data, analyzing it and providing insights to the marketers.
Visitor Relationship Management solution helps in understanding the behavior of online visitors to the website to gain better understanding and optimize the relationship. Visitor Relationship Management provides the ability to customize each interaction with the customer and make it more personalized to increase the relevance of each customer visit and improve customer experience. Visitor Relationship Management solution can help us in achieving following objectives:
- Decreasing the customer acquisition cost by identifying the key channels to target for customer acquisition
- Increasing per customer sales or maximizing return on marketing spend by customizing the offers and deals offered to each of the customers to increase conversion likelihood
- Improving customer retention by identifying content and issues which are leading to customer loss
- Improving customer satisfaction by making customer experience more personalized
- Customizing site design by understanding visitors’ behaviors and needs
How Visitor Relationship Management is solving new types of business problems
Having understood the benefits of Visitor Relationship Management solution, let’s see what are the various data points that can be captured through Visitor Relationship Management solutions which can help us achieve the benefits.
- Visitor’s relation with the company
- Amount of time spent by the visitor on the website
- Number of pages visited by the visitor on the website
- Did the visitor finally bought the product/service or did the visitor finally signed up?
Above is just an illustrative list; there could be several other attributes that could be captured for visitors which can help us in doing effective analysis for visitors.
These data points can help companies estimate and map the entire life cycle of visitors which then serves multiple purposes ranging from visitor acquisition to building retention strategies. It can also help us in building website content which is more appealing, personalized and leads to higher conversion ratio.
Companies can use Visitor Relationship Management to conduct below five key analysis to improve the customer experience and enhance the site design and content.
- Channel Attribution
- Content Recommendation
- Propensity Modeling
- Churn Prediction
Channel attribution, in simple terms, is identifying which are the channels or sources where the company should focus to use their marketing budget effectively and improve the customer conversion ratio. In other words, channel attribution modeling helps us in improving customer acquisition by targeting customers through right channels. With the surge in number of channels and traffic sources, marketers are facing the issue of identifying the right channels to acquire customers. Using Visitor Relationship Management solution will help marketers and companies to identify the right channels and traffic sources which are contributing to the actual customer conversion, rather than an interaction point. Using insights from this analysis will help marketers and companies optimize their marketing and advertising budgets for effective conversion strategy.
Customer or visitor segmentation, in the case of online companies, lies at the heart of making websites and services more personalized. In the era where customers are flooded with different options and website to choose from, it becomes imperative to give customers a much more personalized experience to improve their likelihood of buying more products and increase loyalty. Using data from Visitor Relationship Management solutions and combining it with other visitor data such as demographic and socio-economic data, visitors should be segmented into different clusters, where visitors falling into particular cluster should have similar attributes. One of the examples of a cluster would be a group of customers who have following attributes in common:
- Already registered
- Age group 20-30 years
- Interested in gadgets
- Usually buy mobile phones
- Access the website through apple devices – iPhone or iPad
- Responds positively to discounts
The attributes could belong to one cluster. Similarly, there could be multiple other clusters for visitors. With the advancement in technology, it has become possible to create micro-segments for customers to gather more insights and offer personalized services.
Recommendation systems play a very important role for any website or an e-commerce company. For a website which is mainly into publishing content, identifying which is the most suitable content for a visitor and which content has highest likelihood of being read by a visitor is very important because that defines the time which a visitor is going to spend on the website plus the number of times a visitor is expected to return to the website. For a website selling products, showing the products which the visitor may be interested can provide a big boost to cross-selling. Identifying which content to show or which product to recommend can provide a competitive edge to the company, which significantly translates to improved top line. Netflix is considered to have one of the best recommendation engines and a majority portion of their sales (movies which visitors see on Netflix) are driven through their recommendation system. So, capturing visitor data and using it to identify what is the next best content or next best product for customer can impact revenues and customer experience in a huge manner.
If we could estimate the likelihood of a visitor getting converted to a customer, then in the case of lower probabilities we can further customize and personalize the services to a visitor to increase his chances of getting converted. Visitor Relationship Management solution can help us gather data about visitors and then analyze that data to develop a customer propensity model which will eventually help us to improve the probability of converting a potential lead or a visitor into a customer. This has a direct impact on the top line of the company, where the company is not spending any additional money but using the existing restricted budget.
Churn prediction or site abandonment can be very useful for an e-commerce company. Understanding the reasons why visitors are leaving the site or, even better, predicting what is the likelihood of a visitor leaving or abandoning the website can help the e-commerce company curate the content and design in a way which is in sync with the visitor’s choice and preferences. Churn prediction could be as important as propensity modeling because it helps the company in retaining the customers; the cost of retaining existing customers is less than acquiring a new customer, therefore, it becomes very important to analyze the data to identify customers who have high probability of leaving. Customers who have high probability of leaving can be provided with customized offers or content can be more personalized to improve the impact of website.
There could be multiple other analysis that can be carried out using data captured from Visitor Relationship Management solutions. In order to further improve the results of Visitor Relationship Management, the website or the company needs to integrate Visitor Relationship Management data with other solutions and data points such as customer’s/visitor’s demographics, past purchase history, browsing pattern, socio-economic analysis, visitor’s objective, among others. Creating a comprehensive data lake and integrating Visitor Relationship Management with other outputs will provide a complete and very insightful view of the customer journey.
This article was contributed by Perceptive Analytics. Chaitanya Sagar and Saneesh Veetil contributed to this article.
Perceptive Analytics provides data analytics, data visualization, business intelligence and reporting services to e-commerce, retail, healthcare and pharmaceutical industries. Our client roster includes Fortune 500 and NYSE listed companies in the USA and India.