What pages of an online retail site are most likely to respond to proactive chat (home, product page, customer service, checkout, etc.)?
Our data suggests that the greatest determinant of proactive take-rate is not particular page content, but other factors such as time on site, number of viewed pages, and repeat visitors. For example, visitors invited after 2-3 minutes on site have a 79% greater likelihood to accept than a website visitor who's been on site for less time. Repeat visitors are 64% more likely to engage in proactive chats than first-time visitors. Canadian electronics retailer The Source only invites inside their shopping cart and they experience an over 20% acceptance rate.
We would posit that this is due, not to the shopping cart itself, but because visitors inside the cart have exhibited other on-site behavior which makes them more likely to engage.
What is "rules-based proactive chat" and what are the best practices around employing these rules?
Rules-based proactive chat is the automated triggering of chat invitations based on a pre-defined set of visitor behavior metrics. An internal software engine is constantly monitoring visitors and checking against the rules. Invitations fire when a rule has been met. Depending on what type of site you have, we have reams of best practices which customers can follow. By far, the most important practice is to treat proactive invitations like a science - to test a wide variety of implementations, make changes, and continue measuring. Here's one tip: across our customer base, inviting visitors who've been on site for between 10 and 30 seconds yields a lower acceptance rate than other time ranges (inviting earlier or later both outperform this time range).
What should retailers look for in their web analytics tools to help them understand site behavior and determine rules for proactive chat?
Website analytics and proactive chat go hand in hand, so the answer to this question changes depending on whether a retailer is just getting started or if they've been using proactive for some time. In the former case, one of the first things to look at is average time on site. Because timing is so important for proactive, this metric gives customers a starting place. If you've been doing it a while, more detailed path and exit analysis can greatly influence where and when to invite. New York based retailer Gotham City Online experiences a better than average proactive take-rate of 8%, due largely to their vigilant use of website analytics in conjunction with proactive rule sets.
How can retailers integrate chat with personalization tools to show chat only to their most profitable customers? E.g. account information (purchase history) or clickstream (customer is looking at high margin, high ticket item or customer is returning and has over $X sitting in the cart)
There are many ways to accomplish this type of integration from the simplistic to the advanced. iS3, makers of STOPZilla, use URL parameters to send invitations to certain landing pages. Other customers use regular expression matching to build invitations and rules based on product type, cart amounts, and other variables.
Do you have any tips for writing persuasive chat invitation messages?
The number one tip is to split test messaging by serving two invitations for the same rule. Not all rule engines allow this but for the ones that do, this is a powerful feature. A popular best practice is to send specialized invitations to visitors who arrive on-site through pay-per-click ads shown for competitor keywords. Another tip is to include special offer messages in your invitations. Finally, our research shows that invitations which allow visitors to type in a question directly (via a built-in form) are nearly 50% more likely to be accepted. This seems to indicate that one possible persuasive technique would be interrogatory statements.
Any other comments or tips on rules-based, proactive chat you would like to share?
Many retailers are afraid of this technology and think that it will drive visitors away. Anecdotal information from our [retail] customers, our benchmarking studies and research with internet shoppers themselves refute that fear. Proactive chat drives more interactions, high levels of customer satisfaction, and more sales.