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Automate Social Media Reputation Monitoring

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Introduction

Keeping an eye on all of your social media accounts can be a challenge. With the possibility of hundreds of messages being directed at your accounts every hour of the day, it is important to know what messages can be ignored and what messages need your attention. With the help of Byron Structured tasks, you can automate the process of monitoring your online reputation using real assistants to determine the content of all incoming messages directed at your accounts and process this data in a format that can be integrated into thousands of existing tools that you use on a normal basis. By following these simple steps, you can define what type of information you want assessed and where you want this data to be pushed when finished. Here is how you can get started integrating Byron into your workflow.

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What Are Structured Tasks?

With Byron’s structured task feature, you can automate almost any type of busy work that requires a human. The feature is designed so that you build out an automated process once then can trigger Byron to do the work at any point in time. Watch the video on how it works.

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Step 1: Setup Assistant Instructions

ASSISTANT INSTRUCTIONS TEMPLATE

Please read the following tweet and determine whether the message is positive, neutral or negative.

Tweet Message: 

Twitter Mention String

EXAMPLE TASK WITH MAPPED DATA:

Please read the following tweet and determine whether the message is positive, neutral or negative.

Tweet Message: "Hey @acmeinc, it was great seeing your presentation at AMS Conference!"

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Step 2: Setup Response Fields You Want Back From Byron

Add fields and description on how you want your task completed. Below is an example of how you would set up the fields and instructions.

FIELD NAME

Twitter Mention Sentiment

ASSISTANT FIELD DESCRIPTION

Is this message positive, neutral or negative

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Step 3: Add Data/Tasks

There are two ways that you can send new data/tasks to your Structured Project. You can either upload a CSV file of your variables that you set in Step 1, or you can fire off tasks via Zapier. Below are some popular Zapier integrations that align with this blueprint example.

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New Twitter mention, send to Byron Categorization API, then ping within Slack of any negative tweets.

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New Twitter mention, send to Byron Categorization API, then retweet any positive message.

Through Zapier, you can hook up over 1000+ integrations. Need help with setting things up? Chat with our specialist team to help you set up a custom integration.

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Output From Byron

If you follow the template above Byron would provide an output like:

EXAMPLE TASK:

Please read the following tweet and determine whether the message is positive, neutral or negative.

Tweet Message: "Hey @acmeinc, it was great seeing your presentation at AMS Conference!"

EXAMPLE OUTPUT:

Twitter Mention Sentiment
=

Positive

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Getting Started With Byron

How to get started...

1

Create a Byron account

2

Create a Structured Project with the instructions and snippets above

3

Send data to Byron via Zapier of by uploading a CSV of data

4

Integrate Byron's responses to over 1000 tools via Zapier

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