Predictive Signals

Unlock powerful insights with Zillow’s enhanced client insight tools, now featuring advanced AI and Machine Learning generated insights. By analyzing data from buyer and seller activities on Zillow, you can easily identify key prospects, including those most likely to move or submit a mortgage application. These predictive signals provide a deeper understanding of your clients' behaviors and preferences, allowing you to tailor your approach with precision and maximize your impact.

High intent buyer

Customers who are flagged by our model as a ‘high intent buyer’ are 4.2x as likely to transact in next three months than those who are not flagged. 

To determine which buyers are high intent and most likely to transact in a 6-month period, Zillow’s machine learning model evaluates factors such as their browsing activity on Zillow. Key indicators include time spent viewing homes, the number of homes favorited or shared, and views of agent profiles. This data helps predict which buyers are further along in their journey. 

The High Intent Buyer tag is applied to existing connections received in the past 12 months, considering both Zillow’s model insights and agent inputs, such as Contact Status updates and communication history from the Premier Agent app or connected CRMs. This tag acts as a compass, helping you prioritize clients who are likely to need more immediate support.

High intent seller

Sellers who are tagged as ‘High Intent Sellers’ are almost 3x more likely to transact in a 6-month period than those not tagged.

To determine which sellers are high intent and most likely to transact in a 6-month period, Zillow's machine learning model evaluates many factors including customer’s browsing activity on Zillow.com, if they’ve claimed their home, interaction with some of our seller-specific resources, and much more. 

Most sellers who are tagged as "high intent sellers" will be seller connections delivered to participating partners; however, if a buyer connection's activity has indicated that they are very likely a motivated seller as well, we will tag them as a "high intent seller."

Likely to submit for mortgage

Buyers who are tagged as “likely to submit for mortgage” are determined to have high propensity to initiate a mortgage inquiry with ZHL in the next 30 days.

The model leverages a buyer’s for-sale home page views and buyer preferences, as well as home submits (tours, connect with an agent) to determine how likely a buyer is to engage with Zillow Home Loans about financing within the next 30 days.

Likely homeowner

Contacts who are tagged as “Likely homeowner” are predicted to own a property, helping the agent understand the level and type of support their client may need in the home buying journey. 

The model predicts the probability that a buyer or seller already owns a property, and is not a first-time homebuyer using home saves, saved search, Call or Email Submit, home shares, and total number of off-market home details page views in the past 28 days.

Likely renter

Contacts who are tagged as “Likely renter” are determined to have high propensity to be considering renting, helping the agent understand the client's current intentions and position.

The model leverages a user's views of for rent home detail page, open and click-through rate of Saved Search emails, and more to predict a user’s propensity to make rental email submissions within the next 1 to 28 Days.

For agents using Follow Up Boss, we recommend creating a smart list as a best practice to comb through your pipeline. A smart list is a saved search that highlights the contacts you need to follow up with, and you  can filter by Zillow connections flagged as High Intent Buyer tag, then create action plans based on the status these connections are in your pipeline