Scaling up micro-conversationsHow to effectively engage with more customers using 12Mass

* Please read notes attached to presentation

Communicating with a large audience mentioning your brand while keeping the conversations personal and effective is a challenge.

The problem

Right: A Twitter search for “tesco”

The solution: Build dialogue decision trees.

• Save data of past responses to suggest optimized answers

• Optimize conversations using A/B testing

Respond to all these ‘mentions’ and

A/B test your responses using 12Mass

What is so special about ?• Smart-clustering of tweets• Increases the team’s ability to talk by 100X• Grows stronger the more you use it.

Examples for Tesco:

Group tweets that say (or mean) the same thing, like:

• “I love Tesco“• “I hate Tesco”• “Going to” or “shopping at” Tesco• Checking in Tesco “4sq”• Instagram uploads of Tesco• "I need groceries”• “RT @UKTesco”• “Thanks @UKTesco”• Damaging tweets going viral e.g. toy signage

Social A/B testing

Using 12Mass, A/B test your responses to a typical tweet e.g. “ I love Tesco”

Which of these responses will generate the most engagement?

1. How much do you love Tesco?2. Thanks for the love. 3. We love you back!4. …

1) Thank people for visiting Tesco

2) Apologize for unhappiness caused unintentionally

12Mass Sample Screenshots

1) Save search and responses

2) Sort tweets according to influence rank (optional)

3) Proof-read and edit responses

4) Send out in bulk

12Mass in 4 simple steps

1) Save search and responses

2) Sort tweets according to influence rank (optional)

3) Proof-read and edit responses

4) Send out in bulk

12Mass in HootSuite

Schedule for a live (online) demonstration of 12Mass todaydemo@12mass.com