The modern landscape of performance marketing has evolved quite considerably over the past decade as emerging technologies powered by artificial intelligence have pushed the boundaries of how brands can effectively market their services. This transformation stems principally from the sheer amount of data now available to organizations – both emerging and established – across every industry. Digital advertising teams of today are faced with two options: either they take on the mammoth task of tapping into that data to improve operational efficiency, or, they simply ignore it and run the risk of losing market share to their respective competitors.
This new wave of data is largely attributed to changing cultural and behavioral patterns that are permeating contemporary society. The chief example of this is our increasing use of multiple devices on a day-to-day basis. Each one of our laptops, smartphones, and tablets are generating data that can be captured, stored, analyzed, and then leveraged by companies that have the capability of doing so. In a study conducted by Business Insider back in 2016, it was estimated that by 2020, more than 34 billion internet-connected devices will be installed globally – to put that into some sort of context, that is more than four devices for every human on the planet. Together these devices will truly revolutionize many aspects of our lives both at home and at work.
So, with such vast swathes of information comes the question of how marketers can decipher meaningful insights from all the noise. How is it possible to manage every online touchpoint and create a seamless brand experience for consumers throughout each stage of their journey? The good news is that there are plenty of solutions and strategies designed to help manage all of this. One of the most powerful weapons in an advertiser’s arsenal is dedicated audience targeting – the practice of segmenting desired customers by defined characteristics and then hitting them with relevant messaging at precisely the right time in the buying cycle. If done effectively, this tactic can bring numerous benefits including a lift in conversion rates, a reduction in cost per acquisition (CPA), and an increase in customer lifetime values (CLTV).
In an era when online marketplaces have never been more crowded and consumers have never been more demanding with brands, it’s essential that digital advertisers no longer throw a blanket over audiences. Those days are long gone. Instead, they must be cognizant of the fact that each member of their audience has a specific set of attributes that will influence how they should be targeted.
It all sounds very complex, doesn’t it?
Luckily, our eBook How to Leverage Socio-Demographic and Audience Data for Marketing lays out the steps that can be taken to implement audience targeting successfully. It also takes a deep dive into the challenges to be aware of when working with audience data and the best platforms to use to ensure peak performance. Below we offer a taster of what you can find inside.
Different Approaches to Utilizing Marketing Audiences
Marketing audiences offer a wonderful abundance of insights to help maximize the performance of campaigns across your entire portfolio. To begin, we suggest a few techniques you can adopt to take advantage of the power of audience data:
Google offers a wealth of information about the users visiting your website through both organic and paid efforts. Paying close attention to the demographic makeup of your site traffic can help you build better, more defined, audience profiles which will ultimately lead to improved targeting.
Target Specific Audiences
Once you’re able to paint a clear portrait of your target demographics, you can easily use this information to tailor your ads. There are currently eight major audience types advertisers can use to target and drive peak performance. Due to their large number, few PPC managers have a full understanding of how to utilize them to their potential. The list includes:
- Location Targeting
- Affinity Audiences
- Custom Affinity Audiences
- In-market Audiences
- Remarketing Audiences
- Similar Audiences
- Customer Match
Make Bid Adjustments
Rather than focusing solely on specific customer types over others, it’s possible to target large categories of search users while still prioritizing certain segments that are most valuable for your business. This is done through targeted bid adjustments. Doing this strategically can lift the efficiency of your spending and increase your returns.
The Challenges of Working with Audience Data
While all these options undoubtedly represent great opportunities to move the metaphorical needle in your favor, they do come in tandem with a set of challenges concerned with implementation and optimization.
Efficiency of Spend
Having this bounty of targeting tools makes it difficult to determine exactly how much you should spend on different audiences. Take location targeting, for instance. A business can target several locations with their ads, assigning a constant cost-per-click (CPC), but if you look at how much revenue you derive from clicks in certain regions, there will be some noticeable variations. If you maintain a constant (CPC) across the map, you can end up losing money in certain locations while simultaneously missing out on peak performance in others with a higher revenue-per-click (RPC).
Making Bid Calculations at Scale
Most advertisers feel it’s a question of which audiences they should or shouldn’t spotlight. In reality, though, a wide variety of audiences can have some amount of value when it comes to driving conversions and reaching business goals. For example, let’s say new site visitors show an RPC hovering around $2 while Add to Cart (PLAs) have an RPC over $10. This doesn’t indicate that bidding on new site visitors isn’t worthwhile. It simply means you need to allocate spend toward each audience based on the revenue value they provide. Targeting should always be based on the ROI of each audience. There’s locations, audiences, devices, times of day, days of the week, and other dimensions to segment and assign value to.
The volume of bid calculations and their accuracy are just two of many considerations to make for your campaigns. Other questions that may arise include:
- How often should numbers be updated? So should it be every week? Every month?
- What time period should you assess performance? Performance swings depending on time of the year.
- How do you translate performance differences numbers into bid adjustments?
- How can you be sure to achieve spending and profitability goals with all these bid adjustments?
- Is Google’s Enhanced CPC extracting the maximum?
- What if you can re-use information from bid adjustments across other channels?
- What if you want to control bid adjustments for special events/promotions/tests?
Data-Science Powered Marketing Solutions
In order to make the most of all the targeting options at your disposal, employing automated technologies to help with the workload is an absolute necessity. Here’s why.
In the process of calculating bids, it’s common to be considering factors such as location, device, time, and seasonality. They alone, however, do not represent the end of relevant data points that can influence bidding decisions. Businesses may also want to take into account offline customer data, CRM data, inventory, transactional and POS data, or other engagement data to improve targeting and bidding. That’s where solutions backed by artificial intelligence come in. Through the use of third-party automated bidding technology, it’s possible to unify all significant data to make more efficient and effective bidding decisions.
Unified data is just the first step. The QuanticMind platform, for example, also uses machine learning algorithms, Bayesian modeling, and predictive performance methodology to optimize PPC performance towards specific business goals. After first building predictive models and using optimization algorithms to determine bids that maximize financial objectives, it’s possible to consider location, device, schedule and audiences before automatically calculating bid adjustments. By using the technology, you can be empowered to take advantage of thousands of unique bid adjustments based on targeting data and other dimensions.
Dealing with Data Scarcity
Automated bidding technology also helps glean new insights when data is scarce. Advertisers can target many highly specific keywords or audiences. But there is often very little data illustrating the true revenue value of these low volume groups. Automated bidding technology can use machine learning to accurately predict their value, making robust bids and bid adjustments accordingly.
Audience Data – Wrapping Up
Whether you’re managing the performance marketing campaigns for a small business or an established enterprise, understanding exactly who you are targeting and knowing precisely when to target has never been more essential. Successfully reaching, engaging with, and then converting consumers in the online environment has never been more testing than it is today. Download this eBook to ensure you’re tapping into every available opportunity to leverage audience data and create a seamless brand experience for those interacting with you in the digital space.