Showing posts with label Web Analysis. Show all posts
Showing posts with label Web Analysis. Show all posts

Monday, 19 August 2013

Web Analytics - Repeat Customers

+Adobe  report shows that repeat customers who are 8% of the ecommerce traffic contribute 41% of the sales.

Sale by 1 Repeat Customer = 11 times x Sale by New Customer

+Econsultancy shows that the sales of the customers increased by the repeat of the visits

Sales by Second Time Customer = 3 times x Sale by First Customer

Going by all these metrics its imperative that repeat customers are a Golden Goose. How to keep the customers / make the customers buy again?

Connecting with Customers

Retailers (Online/Offline) need to have constant touch with the customers. They would need to send relevant offers/messages (what is called as Next Best Action today) at right time through right channel
+Yebhi India is an example of badly managed customer interaction. The marketing team bombards the customers with Text Messages / EMails so that the customer blocks the sender / trashes the message once it lands in her phone

A good marketing should take care of the Context and the customer's purchasing power/ intention into account before sending him/her the message

Companies like +Store Express etc provide ecommerce consultancy in this area.  +IBM's
Digital Analytics has powerful analytics tools that can help to create, measure and monitor key metrics

One of the primary channel nowadays is Mobile Anna's Linens is optimizing its ecommerce site for Mobile devices. The Omni-channel approach where the customers to store coupons on the mobile site and transferring back and forth to ecommerce or instore purchases is gaining momentum


Monday, 20 May 2013

How to Get Sales Leads from Analyzing Web Data

Web Pattern Analysis for Identifying Prospects and Products

Web is an abundant source of information. The trails left behind by online shoppers / browsers are as part of Web Log, Click Stream data etc.

This data along with Social Media is fed to the Analytical model which analyses the trend and identifies potential customers / products that can be promoted

There are many companies /retailers that are using Special algorithms / tools to crawl the web and derive useful insights.


Some specialized companies like Palo Alto based Infer (https://www.infer.com/) offer an analysis software that can be linked to CRM system like SalesForce (http://www.salesforce.com/)a and rank the customer



Infer's ranking system uses more than 150 signals , which includes many data feeds - Census, Job Boards, Tweets , Facebook Likes and Comments



There are many algorithms that help in analysing the Facebook data

OpenGraph API is one of them


 See Also:

How to Segment Social Media Users (Influencers / Detractors / Recommenders)

How to measure Price Sensitity of Customers

Segmentation Standards / Framework
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