In the world of real estate SEO it is common to have a large portion of your sales come in through an offline channel. Common offline channels include phone, email, fax or regular mail. Any time your customer places an order for your product or services through one of these channels, you break your web analytics tracking and cannot record key data without a solution.

I managed a search marketing campaign for a B2B online retailer where approx. 55-60% of orders came offline. This presented a major challenge in calculating the ROI of my paid search campaigns. I would spend alot of money to drive traffic to the sites, and was only being shown a portion of the return on ad spend. In fact, I was not able to record over 60% of the orders and revenue that were coming in as a result of our PPC campaigns.

As I came to manage this account and I saw shortcomings of the current analytics program, I began to try to address the problems by doing the PPC ROI formulas manually. In order to calculate the ROI for a PPC campaign, I had to go through 3 different databases (as our websites were on 3 different platforms) and pull the orders, revenue, profit margin, shipping costs and much more from the site backend platforms. Figuring out which sales could be attributed to our paid search campaigns was no easy task. In fact, there were major gaps in the information necessary to properly assess an accurate ROI. I was missing vital product and customer information to be able to establish lifetime value formulas and repeat customer formulas.

I had worked with web analytics solutions before, including Atlas, Clicktrends, and Omniture and knew that we could fix the information gap. I began to push for a solution, and eventually all the major decision makers in the company were on board with a solution that would allow us to gather much more insight into our sales cycle.

Here are the steps we took to implement the offline data import solution:

1. Decide on the Site Functionality – Collaboration between the web dev team, the marketing team and your 3rd party analytics provoder is crucial. You need to have a comprehensive plan on how you will implement, track and test. The first thing you must do is decide how to measure your offline orders. Popular methods include listing different phone numbers on different areas of your site and have a promo or other code generated dynamically and inserted on the site. We chose the latter option. It made the most sense to attach a code to the offline order in the platform database with which to make an association on web analytics side.

2. Implement the Solution on Your Website – Our method to do this included placing a small “generate code” button on the bottom our our e commerce sites. This code would grab information from the session id and URL parameter and create a code based on that info. That info was also recorded by the web analytics platform as well, but we will get to that later. When the customer decided to pick up the phone to place an order, our sales reps would ask them for the code on the bottom of their page. The customer would then click on the generate code button and read back the code. Now there are a few things that can go wrong with this scenario as there is with all offline data solutions. The customer could read the code back wrong, or not see the code. But we made our code a 6 digit hexadecimal code as seen by the customer, so it was easy to read. On the back end, we used a formula to append more information to the code to add some additional information.

3. Set Up the Web Analytics Software to Accept the Additional Offline Information – This is going to vary by the analytics program that you have. Most of the major solutions have ways to import offline data either through an API or through a data upload such as .csv or excel. I used the second option because we had to run additional actions on the data to get it ready for web analytics. Using V Lookups in excel, I would attach the offline code generated by the client to match it up with the correct order. I created the additional variable metrics to track in the analytics software. In this case I was using Omniture, which makes this process fairly painless. I created metrics for revenue, orders, and margin. All the other standard metrics that web analytics software uses such as visitors, time on page, clicks, etc…could be derived by relating back to the code we generated.

4. Test – You will most likely have to iron out a few bugs in the process. Make sure that you double check your metrics coming in against a secondary company ledger or database. For instance, your accounting department will likely have an accurate PO for the product or service sold. Check your revenue imports against the accounting numbers to make sure you are reporting revenue, orders, and units accurately. Also, check your metrics against google web analytics if you are using another analytics solution. Google analytics is free and easy to implement. It is common to have a 10-20% discrepancy between analytics programs based on how that track data. So don’t expect your numbers to line up exactly. If you see a large difference of 40% or more, there is probably a problem and you should investigate further.

5. Optimize – Once you have your offline data solution implemented, you can now start to reap the rewards of your hard implementation work. Work out new formulas to track your ROI by Campaign, adgroup, Product, customer demographics and more. The ability to segment your ROI by different classifications is one of the best analytics features. By pulling in offline revenue and orders into your ROI calculations and online web metrics, you can get a much better picture of your customer and how they are interacting with your site. The result will almost certainly be a more efficient use of marketing funds and more information about your customers wants and needs.

For more information on real estate SEO and real estate analytics check us out at www.realestateseopros.com