A Short Glossary of Metrics for the Digital Agent

Here are some of the hardest-working KPIs that every successful digital agent should have a firm grasp of to enhance their digital marketing strategy.

Becky Poynton
Becky Poynton
May 28, 2021
5 min read
min read
A Short Glossary of Metrics for the Digital Agent

Table of contents


A Short Glossary of Metrics for the Digital Agent

When it comes to metrics, there are definitely those that matter more than others in the real estate sector. Metrics and key performance indicators (KPIs) are not only measurable, but they represent how close or far an agent is to reaching their long and short term business goals. We live in a digital era where websites come with powerful dashboards that can accumulate a lot of data regarding visitor traffic and activity - but it’s crucial to make sense of that data and understand what it’s really demonstrating when it comes to the efficacy of that website. 

Here is a short glossary of a variety of metrics that every realtor should have a good grasp of. 

1. Conversion rate -
studying this metric will let an agent know which channels are performing better in moving visitors down the funnel and which are garnering the most traffic.

2. Cost per lead -
the easiest way to do this is by simple formula (or by using the Cost-Per-Lead Calculator): divide the total marketing spend by total number of new leads, (marketing spend can also include ad spend, third party expenses etc).

3. Cost per acquisition -
this is an important metric to calculate because it will reveal whether or not a certain tool is costing too much to acquire a client that is showing little to no business value, which in turn will affect ROI negatively. 

4. Traffic source -
Extremely useful to understand where people are clicking in from, and with what device. For example, using URLs tagged with UTM codes

5. Appointments generated/booked -
A dip in this percentage is not always a bad sign but can sometimes simply suggest that an agent requires more training or needs to further develop a particular skill. 

6. Exit Points/Pages -
Finding out what the bounce rate is like and at which points visitors are clicking off can help sharpen the efficiency of an agent’s website strategy. If they are finding their way to a sign-up form and filling it out, that’s a good sign it’s working. But if visitors are exiting after the homepage or a blog post, it could be an indication that the website calls for better CTAs or more compelling content.  

7. Client Lifetime Value (CLV) -
Some companies geared towards real estate solutions have even installed CLV calculators on their site, but it’s basically a way to inform an agent of the value of an average client over the course of their relationship. 

8. Email (Open Rates & CTR) -
If open rates are low, (2-10% is respectable), agents can try testing subject lines, while also evaluating the quality of email lists (weeding out outdated or irrelevant recipients). Clickthrough rates will reveal whether subject matter is working and engaging enough for people to not only open an email, but click through to further action. 

9. Client Feedback Ratings -
In 2019, firms reported that about 30% of their sales volume came from past client referrals, and 30% came from repeat business - solidifying the importance of having a solid referral system. Designing a simple, streamlined client feedback survey as part of the sales process or at the end of a transaction process can help ensure that that feedback is helping shape even better strategic marketing activity. 

10. Expenses and Revenue -
This can look different for each agent, but being able to track revenue streams helps identify which areas are doing well, while costs columns can help agents keep a careful watch on where money may be leaking unnecessarily.

For more on how measuring success through data, see our blog post

Related article:

How to Identify and Replicate Success with Data

In property, a lot of information is transacted at every decision point, from the initial search to final purchase, but are we equipped to handle so much data?

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