This post discusses using PixieBrix to capture, annotate, and share customer interaction data throughout your organization.

Amazon and customer obsession

Companies that excel at amplifying their customer’s voice within their organizations provide better customer service and build better products. Consider Amazon, whose first leadership principle is “Customer Obsession.” To glean insight into some of what Amazon does to put this principle into practice, we mined a myriad of public data (using PixieBrix 😎) around CX at Amazon. Here’s a summary of what we learned:

• Amazon CX and sales teams use internal browser-based tools and scripts for collecting massive volumes of customer call, email, and chat data
• One way they’re separating useful information from noise is by mining for keywords
• They’re using customer demographics (e.g., job title) and data around employee skills and focuses to route interaction data to the appropriate destination (e.g., an Amazon Chime room)
• They’re automatically tagging data with important context (e.g., case ID) and web page metadata (e.g., URL)
• They’re quantifying the business impact of these digital tools and processes

At the time of this post, Amazon’s market capitalization was the fourth largest in the world, behind only Apple, Microsoft, and Google. Surely, their tools and processes around customer obsession have been a driving force.

Voice of customer data at your company

Your sales reps, account managers, and CX agents are also interacting with customers every day. These calls, emails, and chats contain data around:

• Product feedback
• IT issues and bugs
• Problems that should be escalated
• Upsell and cross-sell opportunities
• Competitive intelligence
• And so on…

However, capturing and sharing feedback in the moment is tedious and not realistic for a busy front office staff. Therefore, valuable insights get lost in long transcripts and email threads that also contain a lot of noise.

Traditional approaches don’t separate insights from noise

CRMs: CRMs sync 100% of email and chat data out of the box, which doesn’t separate insights from noise.

Alerts: Sales operations teams configure webhooks to trigger alerts and share data programmatically, but these get spammy and miss nuance and context.

Data Science: Data science teams use natural language processing (NLP) to develop customer health scoring models (or word clouds 😜), but this approach alone leaves money on the table.

Imitation is the Sincerest Form of Flattery

PixieBrix is a low-code platform for customizing the user experience (UX) of any web page. The platform comes with a set of building blocks, or Bricks, which users can combine to create custom integrations and workflows.

In light of our research around customer obsession, we’ve released a subset of Bricks for capturing, enriching, and sharing customer interaction data.

Here’s a quick demo:

The PixieBrix approach

We believe three design principles make our approach effective:

1. Users can capture customer interaction data wherever it lives (email, chat, web apps, social media, everywhere)
2. Users can annotate data with context
3. Users can share data in the appropriate location so the right people see it

Capturing Data

We showed two ways of capturing customer interaction data:

1. Right-Click Menu: Using the PixieBrix Right-Click Menu to extract highlighted text. This provides the most flexibility to copy snippets of data from any web page.
2. Button: Adding a button to pull data from a consistent property path on a consistent URL. This is useful for internal tools and web apps when you want to extract the full message.

Annotating Data

We annotated data both manually and automatically:

• Manual: we added written notes and dropdown tags.
• Automatic: we automatically extracted web page context like URL (screenshots coming soon 🏞️). We also automatically extracted user information like PixieBrix profile and timestamp. Additionally, you can extract semantic data, which is what websites expose to search engines.

Sharing Information

PixieBrix users typically send customer interaction data to four types of applications based on who needs to see it and what they’re trying to accomplish:

1. Project Management: Trello, Jira, Monday.com, Asana, etc.
2. Collaboration: Slack, Skype, anything with an incoming webhook
3. Database: Google Sheets, Airtable, AWS S3, etc.
4. Robotic Process Automation: Automation Anywhere, UiPath, etc.

Conclusion

The most successful companies are customer-obsessed, which involves echoing the voice of customer data throughout your organization. PixieBrix makes it easy to capture customer interaction data on any web page, tag it with important nuance and context, and amplify it in the appropriate channels to encourage fast action.

Try it Today

If you’re interested in trying PixieBrix, you can sign up for free at pixiebrix.com.