Techniques for measuring DOOH exposure and mapping to give cross-device measurement more meaning are being utilized by larger brand marketers, but smaller companies are also getting into the game and finding innovative ways to layer maps onto their local strategies.
Here are five ways that marketers can use mapping technology in their local campaigns.
One medium that will be especially helpful in the recovery is connected TV (CTV). About three-quarters of households own connected TVs, so SMBs can easily reach the public through this ad-supported medium as life returns to normal.
There are many opportunities to excel both in the current and post-pandemic marketing landscape, but businesses will only be able to take advantage of them if they intelligently create demand. Because of this, SMBs should use audience and measurement data to inform their CTV advertising strategies as markets reopen.
Let’s face it: Affiliate marketing gets a bad wrap. Once considered a channel fraught with black-hat players, fraud, weak strategy, and an overall lack of transparency, affiliate marketing suffered from a reputation for opacity that did not imbue confidence and trust in partners. Most importantly, there wasn’t a sufficient level of confidence that the channel could deliver desired results and outcomes.
The reality is that the last-click-only perception of affiliate marketing is a thing of yesteryear. Looking back, coupon and loyalty dominated the category because of this reliance on the last-click model embraced by brands. That model stymied the channel’s advancement and progression. However, affiliate is no longer relegated to rudimentary tactics like banner advertising on coupon sites.
What most ad platforms cannot tell you is how your ads drove foot traffic to stores and other physical locations you care about. If driving foot traffic to retail locations is your job, Google Ads and other digital ad dashboards can’t help you. When in-store foot traffic attribution is crucial, how do you solve for it?
In this article, we cover three ways to solve for attribution, ranging in difficulty from easy to hard. We look into easy options that are inexpensive but tend to be unreliable. We evaluate a medium option that has a moderate cost but is highly reliable and bypasses human error. And lastly, we look at a hard option that incorporates several tools and, while highly reliable, comes at a high cost and is difficult to scale.
Marketers surveyed showed an especially keen interest in understanding how they can integrate location data with other kinds of information. Asked how they deploy location data, 27% said it’s a “key component of a broader strategy to map the customer journey online and offline.” Twenty-six percent, the second-largest segment, said they were interested in learning how to marshal location data in conjunction with other data to achieve more advanced goals than their current practices allow.
By facing the harsh truth that we need to lean into disruption – instead of patching up past approaches or creating inadequate work-arounds – our industry will build something better that helps us increase value in our marketing spend. Shifting to CMM would provide a framework to address the full business (not just marketing) needs, and help us all be ready to adapt through data-driven decision making. And when you can adapt, you can build competitive advantage, evolve, and thrive.
Ultimately, ensuring the success of purpose-driven campaigns comes down to building meaningful connections using all the technology, data, and creativity at one’s disposal to reach the elusive double bottom line. Here are four tips that can help marketers tap into data and technology to optimize their purpose-driven campaigns:
Without pixels, marketing in the digital world would be a guessing game. However, with 90% of all commerce still taking place in the physical world, oftentimes marketers find themselves in the dark, not knowing how their customers are interacting with their brands offline. Enter location intelligence, or as we like to call it, pixels for the real world.
Take a moment to reflect on the past few weeks. Did you stop at a coffee shop on the way to work? Did you work out on specific days of the week at a nearby gym? Are there restaurants you frequent when you are too lazy to cook at home? In a study, published in Nature Human Behaviour, researchers found that people frequent up to 25 places at any given time period. Similar to marketing pixels placed on websites, the ability to understand physical, real-world behavior such as path-to-purchase, visitation patterns, day-of-week preferences, and daily activities fuels more strategic decision making.
Location intelligence has become an important but crowded sub-sector of local media and commerce. When it comes to value for retail brands, marketing tactics are all about driving (and measuring) foot traffic. This is where Paris-based location marketing and analytics company Teemo continues to innovate.
As we discussed with CEO Benoit Grouchko on the latest episode of Heard on the Street, the company works with multi-location brands like JoAnn Stores to boost return on ad spend by growing physical foot traffic.
Responsible location intelligence involves practices like “stop data,” to measure users’ location dwell times, and the scale Foursquare achieves in its network of app publishers. Placed is one of the first location data players and a leader in attribution since 2011.
Now that the two companies have come together via acquisition, how does that position Foursquare for interstellar domination of the location intelligence market? It’s about greater capability and scale, say Foursquare’s Josh Cohen and David Shim, our guests on the latest episode of Heard on the Street.
Automotive OEMs have bulk data plans with cellular carriers primarily for collecting vehicle diagnostic data (e.g. mileage, engine warnings, etc.). As a result, it is now possible to capture data from millions of vehicles. This presents an opportunity to capture exponentially larger audio data sample sizes, especially for AM/FM radio, which will fundamentally change audience measurement, ad attribution, and program insights. While data today is primarily audio listening, the introduction of autonomous vehicles will result in significant consumption of video that can be measured in a similar way to audio.
The blurring lines among search, social, and e-commerce only muddy the water when it comes to determining the customer’s journey to conversion. So, how can advertisers accurately attribute their marketing dollars to customer wins? Increasingly, marketers are turning to a multi-touch attribution strategy that includes both online and offline conversions, thereby moving away from simplistic last-touch attribution models.
Good news for the whole location-based marketing industry—a new report from location data firm Factual based on a survey of location data buyers finds the field is getting more effective and better at measuring its results. Nearly 9 in 10 marketers said location data is driving more effective campaigns. Eighty-six percent said it’s growing their customer base, and 84% reported higher customer engagement.
However, while use of location-based marketing is set to grow to 94%, only 24% use it or are planning to use it to establish offline attribution.
Foursquare and Placed are location tech’s new power couple.
The location intelligence firm is acquiring Placed, which had previously been bought by Snap for its top-rate online-to-offline attribution solution, and the two will offer one of the most powerful attribution solutions in the location industry, to be called Placed powered by Foursquare.
As ad tech faces tougher times and a privacy-driven crackdown on data collection and ad targeting practices, more mergers and acquisitions are likely to transform the industry’s terrain. Teaming up and stockpiling as much first-party data as possible, thereby eliminating the need for less compliant modes of data harvesting, will boost the longevity of some firms while others flounder.
Unfortunately, there’s no “silver bullet” for separating good data from bad. Instead, organizations should think of data quality as a habit, with “good” data clearly defined and concrete processes in place to harvest what’s valuable and discard what isn’t.
With that in mind, here are three steps to taking unfiltered data and deciding what to keep — and what to throw out — to achieve optimal data accuracy.