Remove cn
article thumbnail

4 simple strategies for improving customer retention

delighted

While there are different formulas for calculating retention , the standard equation looks something like this: Retention Rate = ((CE-CN)/CS)) X 100. CN = The total # of new customers that you acquired during the period. If that looks a little complicated, don’t worry. Once explained, you’ll find it very simple and intuitive.

article thumbnail

Integrate HyperPod clusters with Active Directory for seamless multi-user login

AWS Machine Learning

amazonaws.com" # The default base DN to use for performing LDAP user operations ldap_search_base = "dc=hyperpod,dc=abc123,dc=com" # The default bind DN to use for performing LDAP operations ldap_default_bind_dn = "CN=ReadOnly,OU=Users,OU=hyperpod,DC=hyperpod,DC=abc123,DC=com" # "password" or "obfuscated_password".

Scripts 77
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

5 Ways a Contact Center Can Help Improve Customer Retention

Global Response

The simplest customer retention rate formula is: ((CE – CN) / CB)) x 100 Let’s break that down: To calculate retention rate, you’ll need to pick a set period of time to measure, usually monthly, quarterly or annually.

article thumbnail

Using Call Centers to Improve Customer Retention and Increase Lifetime Value

Global Response

Customer retention rate is slightly easier to calculate, and can be calculated using this formula: [(CE-CN) / CS] x 100 = CRR That may look confusing, but it’s pretty straightforward. First, customer retention rates are always measured based on a specific timeframe, typically monthly, quarterly or annually.

article thumbnail

5 Must-Have KPIs For a Successful Telemarketing Campaign

NobelBiz

You will pay somewhere between 5 and 25 times more.

article thumbnail

Recommend and dynamically filter items based on user context in Amazon Personalize

AWS Machine Learning

Using contextual metadata to train Amazon Personalize models will help you recommend products that are relevant to both new and existing users, not just from the profile data but also from a browsing device platform.

article thumbnail

Blockchain Futurist Conference, Toronto - Pix, Thoughts and Larry King

Jon Arnold

Great view of our skyline from the back patio - CN Tower and all - cool, huh? I'll have more to say about that in my upcoming post, so for now, I'll share a few photos. I'm not giving you much here, but your thoughts, questions or first impressions are most welcome!

voip 40