When retail brand owners spend on mobile marketing strategies, they are usually looking for success in terms of store walk-ins. Digital data is often not enough to calculate these metrics. This is exactly where footfall attribution comes into play.
Attribution studies are conducted to physically monitor the targeted brand locations and analyse the results in correlation to their mobile advertising campaign.
This means that the study also monitors the impact of mobile ad exposure on users entering the store (exposed group) vs the others (control group).
What is footfall attribution?
Footfall is a marketing term used by retailers for describing the number of customers that enter their stores.
Footfall attribution is a method used to correlate digital marketing campaign impressions to actual store visits.
For brick and mortar businesses that calculate their success based on the number of customers that walk in their doors, this technique offers valuable insights.
Mobile marketing techniques are very efficient in determining the number of consumers who view your ads. However, they are often not sufficient to determine whether the consumer who received the advertisement physically visited the store.
Footfall attribution is, therefore, a clever mix of the results obtained from mobile campaign impressions and the data collected from actual store visits.
While eCommerce sites get their desired results using mobile marketing techniques, brands that have physical stores find it meaningful to utilise footfall attribution techniques. Businesses like restaurants, coffee shops, grocery stores, clothing brands, etc use this technique to accurately measure their sales growth.
Footfall attribution studies provide valuable insight in aspects like competitive analysis, temporal analysis, customer analysis, etc.
Why is footfall attribution needed?
Digital measurement metrics are often an inaccurate way to measure the marketing performance of a store. When retailers solely rely on online figures for campaign performance, they end up missing the real-world business results.
Needless to say, when marketing decisions and strategies are based on faulty results, businesses start getting negatively impacted.
So why does that happen and what is wrong with digital online measurement metrics?
While online measurement systems take into account the conversions made and the revenues generated, they often overlook the other important factors like the changes in the shopping behavior every year.
Physical showrooms are an important aspect, even for online shopping.
It is noteworthy that shopping patterns and behaviors are continuously evolving. New technologies like augmented reality, voice commerce, etc are gaining traction.
Brands need to understand that modern omnichannel consumers prefer a mix of both online and offline experiences.
Footfall attribution is needed to measure the performance and success (ROI) of digital marketing in bringing in traffic to brick and mortar businesses.
Check out some of these stats for more clarity.
- In a survey conducted by Bizfeel, 57% consumers preferred shopping online whereas 31% preferred visiting a showroom, and 12% used both channels.
- About 75% of grocery shoppers like to visit physical stores before closing an online purchase. (Nielsen)
- About 81% of retail shoppers conduct online research before buying. (GE Capital Retail Bank)
- About 51% consumers believe that the major drawback of online shopping is not being able to touch and feel a product. (Bizfeel)
So, why is it important to track footfall attribution?
Reportedly, “only about 25% of the major retailers track store traffic”- Monigroup.com .
Now, this is where all the large retail brands fail. They forget that keeping track of footfall data helps them monitor customer behavior which in turn can help in launching personalised marketing and sales offers.
Say for example, a departmental store has a footfall of 500 visitors in a day. If 100 of them make purchases (offline) while they are in the store, the conversion rate is 20% for that day.
Since the conversion rate will be different for different days, tracking it for a period of time (a few weeks to months) will give you an accurate picture of consumer behavior on different days and times.
Integrating this data with online purchases made on the same days gives the store owner an accurate idea of the consumer behavior.
This valuable data can help you launch more aggressive marketing campaigns for those times when the visitor footfalls consistently drop.
What can retail brands do?
The best thing that retailers can do is to address the online and offline measurement gap.
Marketers need to understand the two crucial metrics here:
- Online research is often followed by showroom visits
- Store footfall is often followed by online purchases
Brands should therefore pay attention to both, mobile marketing and store footfall data to bridge the gap. A combined study of online and offline behaviors can give insights to increase the actual footfall and revenue for brick and mortar retailers.
And this is exactly where footfall attribution contributes. These solutions are specifically designed to consider digital marketing measurements and real-time retail performance.
A fair number of popular retail brands have already started to address this gap at a grassroot level.
Footfall attribution benchmarks
Footfall attribution benchmarks help rank the campaigns in terms of uplift and visit rates.
Key Metrics to measure footfall attribution
1. Uplift Rate
The uplift rate lets us know how effective an ad has been to bring customers to the point of interest (POI). To find the uplift rate, we segment the customers into categories of those who visited your store after, or without viewing an ad. After that, we find their individual percentages.
The uplift rate is considered positive when the number of people who watched the advertisement and visited the POI are more than the number of people who visited the store without watching the ad.
Two thresholds are used to measure the significance of an uplift rate.
A rate of more than the upper threshold shows excellent performance and a rate that falls below the lower threshold shows poor performance and depicts a need to improve.
An uplift rate between two thresholds means satisfactory results.
2. Visit Rate
Customers can be segmented based on the following categories:
- Demographics such as age, gender, or income,
- Buying behaviors like brand familiarity, lifestyle, behavior, geography, etc.
Visit rate is the average number of people by category who visit your store at a specific period.
When it comes to footfall attribution, the visit rate goes hand in hand with the uplift rate. With these two, you can find the number of people who are in your store at a given time, and the percentage who visited your store by actually viewing your ad.
Having the data on visit rate and uplift rates means that you can find out the audience segment that is the most responsive to your advertisements.
Additional information that can be gathered
1. Footfall Trends
These include the following:
Dwell Time: It is the average time that a customer spends in a physical store location.
The Most Active Time: Footfall trends also comprise the time of the day when there are most customers in the POI.
Brand Affinity: For a company selling items from various suppliers, brand affinity tells a business about the brand that the customers are most likely to be attracted to.
Popular Branch: It is possible to know about the most popular branch in your company based on all the above statistics. This further helps in pinpointing the best location to run your company. Further, this data allows you to plan ahead while opening new stores.
Why are benchmarks needed?
More and more retail brands are now considering footfall attribution as a technique to measure their campaigns. However, it is important for them to constantly compare their efforts and results with competitors in their segment to truly understand their performance.
Benchmarks are needed to measure how well their performance is against peers of the same industry as well as to assess if there is additional room for improvements.
How does footfall attribution work?
As soon as a digital ad is served on a smartphone, a device id is saved. These ids are unique for each device and work like a digital signature for the smartphone piece.
Now, when the device owner enters a store, the device id is automatically detected and the footfall is tracked.
So how is this done?
This is possible when the phone has an app which supports a SDK (Software development kit). The SDKs communicate with in-store beacons to identify the location of the phone without the user needing to even open the phone.
So, what is the methodology behind footfall attribution?
Footfall attribution works through the following two processes:
- Data collection:
Accurate location data is the most important requirement of footfall attribution. Service providers need to integrate with app makers to generate precise location data. This can be done using various technologies like GPS, WiFi, Bluetooth, Geotargeting or Proximity targeting.
Proper use of the technologies can not just generate location data but can also attach it to offline behavior data.
Advanced machine learning and Artificial Intelligence (AI) technologies help in creating accurate location-behavioral data that is then used to understand the footfall trends.
In this stage, data is collected to create 1 group with users exposed to the ad (exposed group) and 1 lookalike audience that is not exposed to the ad (control group).
The database is then compared (exposed group vs control group) to arrive at an accurate footfall attribution report. The number of”store visits” are used as the comparison factor to determine the footfall uplift.
Within this stage, data is compared between the exposed group and the control group to check for Uplift & Visit Rate.
How to measure the impact of digital marketing campaigns in driving store footfall?
In a digital world, an ideal marketing campaign involves the following steps:
- Launch a campaign
However, for most retail companies, the cycle stops at targeting. As soon as a marketing campaign reaches the targeted audience, factors like visibility, quality, and timeliness of data gets degraded.
An ideal solution would therefore need to take into account two factors:
- The quality and timeliness of data available when a transition is made
- Re-integrating the data into the digital systems
Absorbing the aforementioned steps into the campaign makes it optimized and available for enhancing future campaigns.
The impact of digital marketing campaigns on store footfall is measured using tools like:
- Store Visits Tool by Google- This tool by Google is used to to calculate the impact that Google platforms like Google shopping, YouTube and Google Ad displays have on footfall in a store. Since google has marked geofences around various major stores in many countries, the tool shows the number of store visits by the location enabled mobile phone users.
- Collect Data Directly from Store Customers- Data can be directly collected by store owners to measure offline conversions. For examples, when customers are linked to loyalty programs, retailers can directly review their purchases. This data can be further assessed through tools like Google AdWords to check the impact of digital ads on actual purchases.
- Proximity Targeting & Attribution Features- Platforms like Knorex’ XPO and proximity targeting that makes the use of beacons or NFC (Near Field Communication) like techniques to track the location and behavior of customers within the store premises.
How do footfall reports optimize your campaign?
To optimize a campaign, it is required to measure the uplift that occurs as a result of the digital marketing efforts.
Controlled strategies need to be implemented. These include the following steps:
Step 1: Serve ads for a brand.
Step 2: Collect Audience data for individuals exposed to the campaign.
Step 3: Match the data with a “control” group whose attributes match with those of the exposed group.
Step 4: Analyse the results of the exposed group and the control group in terms of the visitation rate.
Step 5: Optimize the results.
Case Study from Knorex’ XPO platform
As a case study, Knorex offered services for a digital marketing campaign for petrol stations around Malaysia.
One of the primary objectives of the campaign was to determine the uplift in conversions.
This means gathering and assessing the footfall data in of their petrol stations, after the campaign was launched.
It was, therefore, required to compare the performance post campaign to the historical data.
Further, it was understood that for accurate results, it was required to have a quantified and data backed comparison to check the results of the uplift.
Knorex XPO with their platform integration with MobileWalla worked on setting up the campaign, collecting the data and coming up with results in the next 10 days.
A controlled experiment was designed.
Mobile ads for the petrol station were served. Audience data was then collected for the people exposed to these ads.
Further, with XPO’s unique ability to generate lookalike audience, a “control” group was generated. The characteristics and attributes of the control group were matched with the “exposed” group.
Therefore, the only experimental factor here was the exposure to the mobile ad.
Results were analysed after 10 days of constant testing. The reports suggested that the control group individuals who were not exposed to the digital marketing campaign showed 1.15% visitation rate as compared to 8.23% of the exposed group.
The difference is clearly astonishing!
While most footfall attribution studies sadly end here, the integrated team of MobileWalla and Knorex XPO not just generated the reports but also used the platform for AI driven, automated campaign and adgroup optimization algorithms.
Therefore, the cycle of targeting, attribution and optimization was complete to assess the conversion goals in the real world.
Read more on “how footfall attribution is done with MobileWalla”
How does footfall attribution improve my business?
Footfall attribution addresses a common question that marketers around the world have:
“How well is my advertisement campaign working?”
You see, marketing is becoming more comprehensive than ever. There are a plethora of channels and devices that businesses use to promote their product.
A view or a click on an advertisement can never be considered as a sale in the real world. Companies want to know about the actual conversions that the ads have been bringing.
Furthermore, there can be other questions like which audience segment has the campaign attracted the most, effectiveness of ads when compared to competitors, etc.
Football attribution is a very effective tool to measure the success of a retail business’s promotional campaigns.
Following are some ways that footfall attribution helps your company:
1. Footfall attribution validates the performance of marketing campaign
First, footfall attribution lets you know if the advertisement is worth it. You will know for sure if the money that you have been investing in your campaigns is bringing you the returns.
Additionally, footfall attribution lets you study all the factors measuring the performance of a marketing campaign in-depth. These include:
The Quality of the Campaign: Your campaigns should be giving a scalable value to the people. Your advertisements should be informative or interesting. Footfall attributes let you know if the audience is engaging in your advertisement.
The Value of the Campaign: You should not only be creating ads, but they should convert to sales. It is, therefore, important to know the number of people who visited your location to buy from you. In other words, footfall attribution lets you know if your prospects are only consuming content from you, or are they providing you value in return.
The Impact of the Message: This one combines with the previous two. Measuring footfall lets you know if your messages are interesting to the people. If yes, the attribution takes it one step further to give you insights like if your “Call to Action” is good enough.
The List of the Audience: Visit rate is designed to know the segment of the audience that views your ads and converts. The information helps you decide and plan your future advertisements while analysing the conversions of the present ones as compared to the historical data
The Timing: Factors such as the time your customers visit your store, and even the dwell time are made apparent by footfall.
Campaign Goal and Fulfilments: With many meaningful benchmarks, you can create a significant campaign goal consisting of the number of people you want to reach and the returns you wish to generate.
2. Footfall attribution helps turn customer insights into action
Every company wants to be data-driven, but according to Forrester, only 29% of businesses can connect analytics to action.
You see, attributions can give data, information, or insights. One of the biggest problems with businesses these days is that they don’t understand the difference between them.
Data: Data is the raw fact that can be quantitative or qualitative.
Information: Information is the data that has been read, processed, and organized into a more readable form.
Insights: Insights come when you can analyze and conclude from the information.
The entire idea of footfall attribution is to gain data and turn them into insights. All its benchmarks have been designed to provide valuable insights that can be instantly converted into actions.
Take for example the uplift rate. The data here is the number of people that have and haven’t seen your ad. The information consists of knowing if your ads are effective. Finally, it helps you find out whether the rate of people visiting your store after watching your promotional material has grown.
With all the football benchmarks and trends accumulated together, you will be in a position to analyse whether your advertisements are reasonable and if they are performing to their best potentials.
3. Footfall attribution optimizes campaigns in real-time
The uplift rates, visit rates, and the trends of the footfall attribution help in making a marketing campaign more effective in real-time.
The technology helps you know which segment of your customers is converted through the served ads. Additionally, you will also know how likely people are to visit and at what time they will knock on your store’s doors.
You will even get insights on how much time you can expect them to spend in the POI. Data like these helps in optimizing an advertising campaign in order to bring the best results.
Say that you run a clothing store.
With footfall attribution, you can know the demography of most interested buyers, the brand they like, and the stores they are most likely to visit. You can, therefore, optimize your ads based on this vital information and keep on making more interesting advertisements for people who are most likely to buy from you.
Real-time optimisation is possible because:
- Data can come in very fast/real-time
- Data can be used to further optimize the running campaign such as
- Optimize the delivery time based on popular user’s visitation time
- Measures A/B testing of campaign messages and optimize it
- Optimize the location targeting based on popular locations
- Scale up the campaign by creating lookalike audience with platforms like XPO’s AI driven, automated campaign optimization algorithms
4. Footfall attribution measures A/B testing for your performance
A/B Testing is not just an effective tool for digital advertisements but also helps you compare and correlate between your customers and your store locations.
The good thing about footfall attribution is that it is extremely goal-oriented. The technique not just lets you know about the ads that are performing well but also about the actual revenue that they are bringing in to the firm.
Additionally, attribution is also about studying the segments. You can get some insights about which audience your next campaign should target.
There is no dearth of options for marketers and advertisers when it comes to creating a campaign. There are unlimited options for delivery and a wide range of choices for media devices and channels.
All said, it still boils down to the single most common question- are your marketing techniques really delivering the results?
It has, therefore, become vital to use attribution techniques to understand the impact of ads on consumer behavior and store visits. As a retail marketer, it is important that you leverage footfall attribution metrics to analyse your campaign and optimize it for best results.