As modern technology solutions are providing you in-depth data to analyse your ad campaign
success and failure on to social media or digital platforms, it also enforces OOH solution
providers to take deep dive into it. As digital out-of-home (DOOH) media network, you want to
improve advertising performance and profits. You want to provide fine grained responses to your
customers in a way that they can absorb it easily. You want to win more business opportunities,
campaigns and confidence of your customers by giving them data insight.
I am sure that you’ve been to public places like central parks, museums, shopping malls, airports, or office buildings, then you’ve seen a digital out-of-home advertisement. This rich, dynamic content is delivered via networked digital signage displays.
advertising is expected to become more than $45 billion industry by 2019 as per prediction of
market research and analysis labs.
According to PWC, in 2015 advertisers spent an estimated $10 billion on digital billboard advertising, yet so many of them struggle to determine what their ROI is, and a lack of data limits DOOH networks ability to compete with other channels and bring in more advertisers. Analytics are crucial to the advertising industry because they enable advertising performance to be measured and improved. Online advertising has platforms like Google AdWords and other online tools, but until now DOOH has lacked a similar platform
It’s time for DOOH to join the 21st century. Other modern advertising channels like search and social media use analytics to derive the success, and VSwank believes that DOOH should do this too.
analytics work for DOOH?
There are 3 stages and data to be collected for all 3 stages. These 3 stages are connected to the life cycle of the Ad display on to the digital signage.
Ad Creation Stage
Data to be collected for the ad which is being displayed. Need to capture ad meta data, ad location and ad time. All this data will be pushed to content delivery network and databases Down the line, it will help the customers derive or predict the ad effectiveness.
Ad Display & Engagement Stage
Need to engage people who are roaming around or close to the digital signage. This can be achieved by providing the free coupons on to the ad, proximity sensors or miss call concepts. This data captured can be utilised to predict how many impressions or engagements an ad had. Even conversions can also be tracked using technology solutions.
Ad Data Prediction and Optimization Stage
Data collected in previous 2 stages are analysed using machine learning and artificial intelligence algorithms. It helps the DOOH providers to make the ad campaign effective and successful. It can also predict when to publish the ads on to the digital signage. This data is the combination of previous 2 stages to better understand consumers and deliver more targeted, personalized content to them. It can only be found in DOOH analytics platforms like VSwank. Prediction and Optimization will lead to optimizing the ad campaign for the customers and end users. This would solve the most complex problem in OOH industry of what to show, when to show and who to show in DOOH industry.
How can analytics help
increase Return On Investments (ROI)?
predicted data can change the way people look at DOOH or OOH. It will redefine the
business model in OOH industry and take the industry on a long journey of success and
innovation. Predicted and Optimised data enables a major milestone in
The ability to change content on any DOOH display depending on who is standing in front of it. This means that the DOOH industry can run real-time targeted ads, just like online.
content will change depending on what locations or websites you have been to previously, the
number of times you have seen an ad, what ads you have engaged with, and more. This makes
your DOOH advertising efforts more effective than ever before. If end users are given the
options based on their interest, demographic and historical background, it will lead to
better or improved ROI.
on DOOH and will provide tools to collect, process and analyse/optimise demographic and
historical data of the end users.
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