title: Cluster Analysis using R for large data sample
body: <p>I am just starting out with segmenting a customer database using R I have for an ecommerce retail business. I seek some guidance about the best approach to proceed with for this exercise.
  I have searched the topics already posted here and tried them out myself like dist() and hclust(). However I am running into one issue or another and not able to overcome it since I am new to using R.
  Here is the brief description of my problem.
  I have approximately 480K records of customers who have bought so far. The data contains following columns:</p>
  
  <ul>
  <li>email id </li>
  <li>gender</li>
  <li>city</li>
  <li>total transactions so far</li>
  <li>average basket value</li>
  <li>average basket size ( no of item purchased during one transaction)</li>
  <li>average discount claimed per transaction</li>
  <li>No of days since the user first purchased</li>
  <li>Average duration between two purchases</li>
  <li>No of days since last transaction</li>
  </ul>
  
  <p>The business goal of this exercise is to identify the most profitable segments and encourage repeat purchases in those segments using campaigns. Can I please get some guidance as to how to do this successfully without running into problems like the size of the sample or the data type of columns? </p>