The holy grail of advertising is solving the disconnect between online marketing and in-store purchases. "While we expect $150B more to be spent online between now and 2018, we expect $300B more to be spent offline in that same time," states Forrester's Sucharita Mulpuru.

We know e-commerce is growing leaps and bounds, but the retail store is far from dead. For advertisers, solving the attribution gap between online marketing and store sales is paramount.

Let's go over some old, new, and emerging trends that will help bridge the online to in-store gap.

Store Locator Conversions

The store locator page on your website is a crucial landing page when search users are targeting micro-moment keywords like "denim store near me" or "ice cream store close by." Placing a pixel or tag on your store locator search box when a user types a ZIP code or location will give you a key micro-conversion of how many users intend on visiting a store.

Using this data, we can infer assumptions like potential store visits and average store order value to tie into a return on ad spend (ROAS) or cost per store locator. For example, say 100 searchers clicked my paid search ad and 75% of those searchers went to locate a store on the store locator page. We can assume 50% of those searchers ended up visiting a store and 75% of those store visitors purchased an item. Using the average store order value of $100, we can determine revenue.

Now, we have all the data we need to back into a ROAS or any other KPI you desire. This method is far from perfect, but it gives you an idea using first-party data and assumptions of what's happening in your search-to-store campaigns.

Google's Store Visits Beta

In our example, we made a lot of assumptions coupled with first-party data. Google has been investing heavily in new technology that attempts to crack the code of how many visitors and revenue are driven by paid search ads.

One new initiative is the Google Store Visits Beta, which works like this: After clicking on a paid search ad, Google will determine a store visit based on the user's proximity to the advertisers location on Google Maps. Store visits takes advantage of the store's Wi-Fi signal strength and can measure signals to differentiate between visits to the store versus visits to the store immediately next door.

Knowing how many searchers visited your store due to paid search ads, you can attribute an arbitrary value of how much that's worth to you. For privacy concerns, Google uses anonymized, aggregated user data and extrapolates it to the broader population.

Given this technology is new and in beta, it will require more testing and time to get an accurate reading of store visits from your AdWords account, but it's an exciting beta that's trying bridge the gap.

Barcode Tracking

This technique has been around for a while and relatively straightforward to implement.

Dedicate a landing page for paid search efforts only. Drive your search-to-store intent keywords' traffic to the landing page where users are shown a barcode via mobile phone or give them the option to print one and bring in-store. Using your store's barcode scans, you're able to tie paid search efforts to get a clear reading of orders and revenue brought in by this effort. The only issue with this is that most likely you will need to offer an incentive like a coupon for the user to print or show a barcode.

Advanced Data Collection Providers

On the forefront of solving the search-to-store gap are data collection technology companies like Datalogix and Acxiom (LiveRamp). In a nutshell, these companies work by integrating with your point of sale terminals and a platform like Google AdWords.

Data providers use third-party data, cookie data, loyalty cards, credit cards, and social media logins to match a user who clicks on a Google paid search ad to an item bought in-store. Many details like emails, credit cards, and addresses are collected during the in-store checkout process. By matching this anonymous consumer information from the data providers to Web-based tracking cookies, Google and these providers can determine how many products were purchased by people who clicked on a given ad and how much more money they spent than consumers who didn't.

At Elite SEM, I have worked with advanced data collection providers to help clients bridge the online to offline gap, since many of our clients' sales occur in-store. Without the use of this beta technology, we were unable to fully assess the success of an online campaign because we were not factoring in-store purchases along with the online sales.

What we once thought didn't work online ended up working very well for store purchases, so changed the allocation of how we budgeted our paid search efforts.

The setback with working with these technologies is that they require substantial investment and integration. In addition, data providers identify approximately only 30-35% of online cookie pools that are matched by tracking sessions from offline sales data via loyalty cards, credit cards, and other POS information.

Another interesting area of advanced data collection are beacons. Beacons are Bluetooth-enabled devices strategically placed in stores that have the ability to communicate with shoppers' smartphones.

Beacons can be used to custom message shoppers, offer discounts, and geo-pinpoint the exact location of a shopper in the store. Data collected from beacons can be used for a multitude of reasons. One of them being an integration with data collection companies such as Datalogix and Acxiom that will provide more accurate match rates.

The current obstacles with beacons are the numerous steps involved to use them. A store visitor must download the company's app and ensure Bluetooth is enabled for it to work.

Best-Practices for Search-to-Store Paid Search Campaigns

To maximize your paid search efforts for search-to-store success, you must have the following account structure and optimizations in place:

• Break out campaigns by DMA or city and geo-target a radius around your stores using location bid adjustments via location extensions. For example, you want your ads to be higher in the search page for searchers within one mile of your store location versus 5 miles from a store location.
• The ad copy you use in your search text ads should speak to a potential store visitor. For example, "Shop in-store for 20% off." Use location extensions to provide information on how to get to your store. Or use call extensions if a searcher needs more information. The store locator landing page should be user-friendly, so users can easily locate a store.
• Keywords should be geo-modified. For example, "sneaker stores in NY" or "ice cream store near me."
• Use Local Product Listing Ads to drive users to local stores that carry specific inventory

The future looks very promising for advertisers looking to bridge the attribution gap from their online initiatives to in-store purchases. Data-collection technology still need to advance to be able to accurately bridge the gap, but for now the above-mentioned techniques will get you to a better place.