After Point-Of-Purchase Advertising International (POPAI) published a comprehensive study of in-store advertising in convenience stores in 2002, little doubt remained that at-retail advertising was an effective way of boosting sales and building brand equity. Retail marketing strategies, from window signs to point-of-purchase displays, were shown to deliver an average sales increase of 6.5 percent across a diverse range of product categories, with 12 of the 38 studied brands experiencing more than a 20 percent lift through the duration of the study, according to the report. At a cost per thousand of between $1 and $9, at-retail media was demonstrated to be one of the most affordable forms of advertising around.
To come to this conclusion, POPAI deployed a small army of auditors and analysts to review in-store merchandising practices and pore over years of sales data, and then employed sophisticated statistical analysis techniques to split their numbers by store, chain, category, and brand. Unfortunately, many of us who are tasked with measuring the impact of point-of-purchase (pop) advertising lack the manpower, and sometimes even the raw data, to employ such a technique. But with the right tools, a bit of cleverness, and perhaps some outside help, solid and informed conclusions are within our reach.
Method 1: Read the Logs
Most of my time is spent analyzing the effectiveness of digital signage (DS) networks in retail environments. Since DS log data is stored centrally, this affords me several benefits not available to the folks behind the POPAI study. Most notably, I have a complete history of every content segment ever played on every screen in every store that I'm studying. These data allow me to create complete historical models of which brands or products are represented in different parts of a store during different times of day, days of the week, etc. With access to my retailer's traffic data or register receipts, I can also calculate the specific effect that a content segment has on close-in sales, along with making projections about how the messaging impacts longer-term buying patterns.
While the amount of data can make this a daunting task at first, patterns emerge over time that allow you to take some shortcuts, while still reaching accurate conclusions. For example, while testing a network of self-service kiosks in a chain of 310 retail stores, one of our clients was able to make statistically significant predictions by monitoring a set of only 10 representative stores. By doing so, the client significantly cut down its research time and costs without lessening its decision-making abilities.
Method 2: Ask the Viewers
Not all digital media networks are built alike, though, and network managers who lack the ability to generate comprehensive playback reports must turn to alternate methods. John Kyle, owner of Kyle Private Networks, has battled this problem since 2003, when he acquired PharmaSee TV and BEVision from in-store TV network operator rms. The two networks comprise more than 1,000 screens deployed in retail locations across the country, powered by one-way satellite connections that can't provide any information about playback frequency or impressions delivered.
To compensate, Kyle asks his stores to provide playback affidavits, and has developed a series of questionnaires that are mailed or faxed to his locations every few months to glean additional information about how his networks are perceived by store patrons and employees alike. While a decidedly low-tech solution, the data gathered through this channel have been invaluable to Kyle's content development team. For example, after one round of surveys, 95 percent of respondents cited employee education as a key benefit of the systems, especially in stores that sold multiple brands of products that seem largely undifferentiated to the untrained eye.
After learning this, Kyle and his team started to produce segments focused more on educating employees about key products. A re-evaluation several months later indicated that their reactive technique was the right one: On average, the new content produced a 30-35 percent lift in sales of the advertised products, based on signed affidavits from the owners and managers of 56 stores representative of the entire chain. Sales data for both the test and control group stores were compared against the previous year's data to help identify and eliminate any natural fluctuation in sales of the tested products. Additionally, more than 10 separate product lines were tested this way in an attempt to get more accurate results about the impact of in-store media in general, instead of its impact on the sales of one particular type of product.
Method 3: Call In the Cavalry
Without a networked digital signage package that allows for playback logging, tracking the performance of large networks can be difficult. But some companies have found success by turning to firms like Arbitron and ACNielsen, which are normally faced with the even larger challenge of tracking nationwide TV and radio networks. Take Accent Health, for example. This firm provides a health-oriented narrowcast network that reaches some 10,000 doctors' offices and health clinics. Relying on a "sneaker net" of couriers manually distributing DVDs to each location every month, Accent Health has no way to directly measure the number of impressions it delivers.
Instead it's turned to Nielsen New Media, which tries to find creative solutions for measuring the impact of nontraditional media. Since it would be logistically (not to mention financially) challenging to directly measure all 10,000 viewing destinations for things like dwell time, impact, and recall, Nielsen instead compiles a statistical average based on observations from a much smaller group of representative locations. Depending on the exact nature of the network being monitored, Nielsen might deploy secret shoppers, exit pollsters, or even electronic surveillance equipment to gauge how target audiences perceive and react to the content being displayed.
Regardless of which method you ultimately choose to track your in-store media, the collected data aren't going to do you any good unless they're actually used to improve your network over time. Kyle Private Networks was able to achieve dramatic results using simple questionnaires, and saw a positive return on investment on their efforts in only a few short months. As John Kyle says, "There's no denying it: In-store TV works." My slightly different spin on it would be this: If you're willing to work for your in-store network, your in-store network will work for you.