Zingtree Tags: customer language

Automatically Including Location Data in your Decision Trees

Zingtree can tell a lot about your end-users just by gleaning information from their browser. For example, you can determine their preferred language, and where they are located.  Zingtree gives you an option to collect this information, and use it in your decision trees.

For example, you can pre-fill a Zip code field in a Data Entry field, or use Logic Nodes to branch to a node depending on the end user’s language or country.

Using the Collect Location Data option in the Settings tool, you can gain access to the following information:

  • Language
  • City
  • State/Region
  • Country
  • Zip or Postcode
  • ISP
  • Origin/domain of server
  • User’s IP address
  • User’s browser type

Getting Set Up

Adding this data to your Zingtree session is easy. Here’s how to do it:

  1. Select your tree, and go to the Settings tool.
  2. Select Collect Location Data.


    If you want to do this for ALL your trees, also click on all my trees. (You can disable enhanced data collection on all your trees in the same way.)

  3. Click Update Settings.

From now on, any sessions with your tree will also include these variables:

  • zt_language (The 2 letter code of the user’s preferred language. “en” is English.)
  • zt_country
  • zt_regionName (this is a USA state)
  • zt_city
  • zt_zip (also Postal Code)
  • zt_isp (the user’s Internet Service provider)
  • zt_org (the origin domain of the user)
  • zt_ip (the user’s IP address)
  • zt_browser (the user’s browser type: IE, Firefox, Chrome, Safari, etc.)

When you examine a session (like from the Sessions List report), you’ll see these variables as a part of your session, like this:

 

Got any cool uses for this? Let us know!

The Best Way to Write Question & Answer Nodes

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Poorly written questions in your Zingtree decision trees can often lead to confused customers and incomplete results. A truly effective node will guide your user through a self-service experience that results in solving their problem or finding the correct answer to a question.

We break down some of the top ways to write powerful, practical questions that will help guide your customers through your decision trees, resulting in a positive and helpful experience for everyone!

1. Keep your questions simple and focused.

It’s important to avoid writing leading or loaded questions that could potentially steer your audience in a new path, or evoke an emotional response that could affect their answer selection. Additionally, long drawn out questions with unusual sentence constructions, and those with double-negatives, can often confuse your customer and lead to misinterpretation.

Keep your decision tree questions as simple as possible by focusing one one subject at a time, and structuring them in an easy-to-absorb way.

Bad: If our customer support knowledge base was not helpful for you, would you, or would you not, consider switching providers to solve your question or issue?

Good: Would you consider another service if you could not self-solve your problem using our FAQ?

2. Speak your audience’s language.

Every customer that goes through your decision tree should be able to easily understand the questions involved and select an answer that makes sense to them.

It’s always smart to avoid industry-specific or too-technical jargon to keep things as clear as possible. This sounds easy enough, but it can take some serious planning to reduce the messaging in your questions to speak the language of your customer while still conveying the general meaning.

Bad: What problems are you currently experiencing with our service or your account?

Good: How can we help you? Please select an option below. 

3. Write with an active voice.

Active voice is a direct, concise way to craft decision tree question and answer nodes. This style of writing clearly identifies the action and who is performing that action so that you can avoid wordy questions, and sounds stronger and more direct than a passive voice.

Active voice most closely resembles how people actually speak, which makes it much simpler for your customers to read through and understand.

Bad: Our recommended guidelines and instructions for solving your issue should be followed as written below.

Good: Follow our recommended guidelines below to solve your issue!


 

Taking the time to construct simple, concise, helpful question and answer nodes in decision trees will open up new opportunities for your audience to self-solve and connect with your brand.

Check out the Zingtree Gallery for live examples of decision trees with quality questions and answers!