Category: Marketing & Advertising

Whether it’s running effective ad campaigns or crafting the perfect message, market segmentation should be a fundamental part of every strategy.

You have spent the time building a B2C or B2B marketing strategy, and now it’s time to make sure that it resonates with the right audiences.

As audiences get bigger, it can be easy to overlook the value of clear and concise messaging. The bigger an audience, the more diverse the needs of that audience are, any digital marketing course will tell you that. That’s where market segmentation comes in, allowing you to focus your B2B marketing efforts on specific segments.

Segmentation provides an edge over the competition as you can prove that you understand who your audience is and what they need most.

What is market segmentation?

Market segmentation is the process of dividing audiences into smaller groups that share the same characteristics to optimize marketing and advertising and sales results.

This practice is a standard business practice that involves identifying key traits that group audiences and using these to build more specific audiences. Market segmentation also allows brands to create more personalized ads, marketing, and sale journeys.

At the heart of this is the idea that consumers are likely to respond to more personal and customized messaging and campaigns. As a marketer, it’s hard to appeal to your entire audience with a single message. Some might respond differently to a specific message. That’s why market segmentation is essential – it the method of segmenting audiences to provide a more tailored solution.

Types of market segmentation

There are many types of market segmentation. Generally, these methods can be defined into four main categories.

Geographic

Geographic market segmentation is the process of targeting consumers based on a defined geographical boundary. Consumer interests can vary dramatically between different regions, and often preferences can be similar across smaller geographic areas.

Sometimes this process of market segmentation can be a simple as weather associated with a geographical location. It wouldn’t be very productive to sell warm clothes to a region where temperatures are low year-round.

Broader regional segmentation includes looking at countries, cities, and postcodes to group audiences. Specific postcodes can determine household income and even interests.

Geography goes hand in hand with both language and culture. Understanding and segmenting your audiences based on location can help to convey the right message (think soccer in the US and football in the UK).

There are many ways of understanding location, from surveys and addresses through to more up to date and accurate solutions such as location data providers.

Demographic

Demographic segmentation is a powerful way of creating specific audience segments that share similar preferences and requirements.

This form of segmentation is a standard method as many targeting and adtech solution provides some way of doing this when building audiences. It’s essential to do the same to your audiences or customer base to segment effectively.

Traditional demographic breakdowns include age, gender, marital status, occupation, education, income, race, nationality, and religion.

Demographic market segmentation is vital to finding product-market fit, but it’s also a powerful way to determine which channel is the best fit. Optimizing channel delivery relies heavily on reaching the right person in the right medium. Demographics are a great way to do this.

Media consumption changes significantly between demographics, so it’s essential to use this form of segmentation effectively to engage your audience the right way.

Behavioral segmentation

Segmenting audiences based on behavior is a popular solution in today’s digital world. Improvements in technology have enabled more touchpoints with greater detail into how audiences behave.

Behavioral analysis provides more options for market segmentation based on how audiences interact with your business. There are many behavioral-based traits to segment audiences, including:

• Web activity – how consumers behavior on your website is valuable behavioral data. Segmenting audiences based on time spent, which pages they visit, and other measurable traffic insights is a powerful way to divide larger audiences into potentially effective smaller segments.
• Usage with your current product or services. These includes app usage, platform usage, or perhaps just the fact that the person has purchased the last three versions of your physical product. These factors are a great indication of loyalty and where consumers sit in the funnel.
• Offline behavior – movement data can help you to understand behavior in the real world. This an effective way of building segments that are grouped based on real-world movement. Segments such as gym-goers or coffee drinkers are powerful as they combine behavioral and geographical elements.

Psychographic

This method of market segmentation is focused more on the intrinsic traits of audiences. It’s similar in a way to demographic segmentation, but it’s more concerned with the emotional and other underlying factors that audiences believe in.

These kinds of insights can be valuable in understanding the motivations, needs, and exact preferences of audiences to create highly personalized segments.

Psychographic traits include personality, values, motivations, opinions, and lifestyle choices.

There are many ways of collecting this kind of information, including surveys or in some sort of feedback process. But offline and online behavior can also be a good indicator of psychographic traits.

Why market segmentation

So now you are aware of the four main methods of market segmentation. It’s time to understand why it’s worth doing. Many marketers identify improved audience segmentation as the most critical priority. Market segmentation offers many benefits to publishers, marketers, apps, and other businesses.

Improves the effectiveness of advertising campaigns

Market segmentation can help to improve marketing activity and advertising campaigns by reaching the right person with the right message at the right time. Segmenting your audiences allows you to provide more personal and engaging advertising, rather than a one size fits all approach.

Targeting a specific audience allows you to tailor the message and timing so that the audience is more likely to respond and engage with your campaigns. Targeting your entire audience with a single campaign is hugely wasteful. A considerable amount of the audience will not be relevant to the campaign, and thus you will be wasting revenue.

Essentially segmentation means that you can remove the irrelevant consumers from this audience, ensuring that you optimize ad budgets, increase ROI and improve the effectiveness of advertising campaigns.

Even if your product or service sits across a broad audience of potential customers, it’s still essential to segment audiences. Some messages will sit better with different segments and work better across different channels, even if the product is the same.

Informs new products and product development

Segmentation is also a useful tool to drive product innovation and can help to hone product strategy. These insights means that product teams can create products that better fit the needs of their customers.

Market segmentation can also identify a need for more specific products that sit in smaller groups within your customer base. Segmenting products is powerful because it helps to sell more and will make customers happier.

Helps to identify new audiences and segments

This process is useful when looking at maximizing the effect of your marketing strategy, but it can also be valuable when looking to grow and scale.

Segmenting your current audience can identify new traits that you didn’t know existed. Seeing this can open up new opportunities related to the newly identified segment. These opportunities can lead to new, engaging marketing campaigns or can even lead to the inception of new products and services that are in need but not currently offered.

Improves business functions and can help to make big decisions

Market segmentation can help a business to understand precisely what their customers want and focus their efforts on these to create a highly specific and valuable product or service. This specification could significantly improve brand perception, lead to more sales, and increase repeat business and engagement.

These insights can lead to better decisions across the business. From product-market fit to product delivery and communication, market segmentation can help to identify the best ways to go about these important issues.

Audience segmentation can also help with decisions such as pricing and can even help inform dynamic pricing strategies.

Common mistakes

There are some common pitfalls that you should look out for when creating your market segmentation strategy.

Too small segments

The most common problem is that businesses go a little over the top with segmentation. Set too many parameters with too much detail, and then end up with a tiny audience.

This mistake means that you will eliminate audiences that don’t fit into your filter but still carry purchase potential. As well as this, you will lose the opportunity to gain quantifiable metrics and insights into specific audience segments.

Make sure you think carefully about how to segment your audience. One or two filters work best, depending on the size of your total audience and total addressable market, of course. The sweet point between segmentation and scale is extremely valuable if you can find it, so be sure to experiment extensively!

Not up to date

Predominantly in the world of traits of digital marketing and advertising, a common mistake is that marketers identify key audience segments that work for their business. But they fail to update these as the needs and products change over time.

Always stay on top of your strategy and constant update and tinker with new methods of segmentation.

Targeting segments that don’t convert

Another common mistake is to identify segments that are both large enough and up to date. But these segments still need to carry conversion or purchase potential.

If the segmentation method creates a group that is not a good product fit and does not have the necessary buying power, then the ROI will not improve just because the audience is segmented.

James Ewen

James is the head of marketing at Tamoco

Advertising can be a challenging endeavor. Carefully crafted campaigns can often fall short of desired goals, with no apparent reason. Marketers can easily reach the wrong audience or fail to deliver the correct message that can covert or engage consumers.

Today, random targeting is a thing of the past. Marketers have a variety of methods to ensure that the right message reaches the right person at the right time. Advances in behavioral tracking and the increase of powerful datasets have enabled advertisers to boost conversion rates across both online and offline campaigns.

Campaigns that use behavior tracking and utilize behavioral targeting are yielding incredible results.

What is behavioral targeting

Behavioral targeting is a marketing strategy that uses historical behavior to personalize the types of ads consumers see.

Historical behavior is sourced through powerful datasets that illustrate how audiences behave. Marketers can then use this to create ads and campaigns that match each consumer’s actual behavior.

Behavioral targeting involves building up a detailed user profile and using this to deliver better messaging and better timing. It limits the possibility of advertisers delivering irrelevant ads and helps to boost advertising campaign KPIs.

What are the benefits of behavioral targeting

Behavioral targeting is a powerful marketing tool that is rooted in the modern, data-centric world that we live in. But it isn’t all about using numbers and tech. Behavioral targeting provides value to both advertisers and consumers.

Advertiser benefits

Improved engagement for advertisers

Understanding consumer habits helps advertisers to identify audiences that have engaged with specific products or touchpoints. It also helps to identify audiences that are in the right moment or behavior for a particular campaign. Targeting users with no behavioral intent or brand awareness will limit engagement. Using behavioral targeting will increase a number of critical metrics, such as clicks or conversions.

Matching consumer needs with creatives and messaging

Personalized messaging converts more users and ultimately reduces the amount of wasted ad spend. Relevant ads are much more likely to move consumers along the purchase funnel than generic ads that are not personalized. Ads that align with a consumer’s previous behavior are much more likely to convert than ones that don’t.

Improving the bottom line

Ultimately advertisers want to get the best possible return on investment on their campaigns. Delivering ads that match with audiences previous behavior is more likely to drive conversions than ones that are generic. With behavioral targeting, companies can see a rise in new business, repeat customers, engagement, and other key metrics.

Consumer benefits

An improved ad experience

Consumers aren’t always keen on giving up their personal data. But they also dislike ads that aren’t relevant or ads where the experience is unengaging. That’s why, when surveyed, more consumers prefer personalized advertising. This personalization ultimately improves their experience.

Better efficiency

Ads can be a quick route to purchase, providing a fast way of identifying the best product for their needs without a long searching process. This increases efficiency for consumers, allowing them to get to storefronts quickly and finding the most relevant products, rapidly.

Awareness of new products

By seeing ads that are personalized to them, consumers can keep up to date with new products that interest them. Retargeting based on behavior can also help to complete purchases that a user was distracted from.

Publisher

As well as behavioral targeting benefits the advertiser and the consumer, it also helps the publisher. Where these publishers use ad monetization as a revenue stream, the ads mustn’t be irrelevant to the user as it might reduce engagement with their product, app, or publication.

How does behavioral targeting work in 2021

The process of behavior-based targeting on the highest level consists of collecting information about a user or a person and then using this information to deliver ads that match this information.

Collecting information can be done in many ways, and it can come from many different sources. Often a data management platform (DMP) is used to aggregate this information for advertisers.

Here are some common data sources that are used for behavioral targeting:

• CRM
• Apps
• Websites
• Marketing systems
• 3rd party data providers
• Marketing surveys

These sources provide a huge variety of data that includes:

Website cookie data

Data on how users behave and interact with websites is a valuable method of behavioral segmentation. Users spend a lot of time browsing the web, so the information is rich – pages visited, for how long, in which regions. Therefore these insights can provide a lot of information that is useful to boost engagement and conversions.

Mobile device data

Cookies also work on mobile devices. Understand the behavior of the potential customer on a mobile device can help to understand which format and which message could work best in an advertising campaign.

These web-based insights can be combined with social signals, check-ins, and mobile purchases to understand the best way to target audiences.

Geographic location

Anonymized location can be extremely valuable for advertisers. Especially when accurate and precise. Since the early days of bidstream datasets, device behavior can be accurately tracked to build up detailed profiles of behavior than can form powerful, behavioral-based segments for advertising.

Subscription data

Businesses that have some log-in system require the users to enter details and information about themselves. These fields can be used to understand the users, with address, interests, and contact details help with behavioral targeting. Let’s say you are looking to purchase a Notion template, it makes sense to pre-fill any forms with relevant subscription data, if you have it.

Demographics

DMPs and other marketing software can collect large amounts of demographic segmentation information, such as age ranges, interests, and gender, to create a detailed profile of audiences. This process usually works without using personal information but these ranges are used to create campaigns that can communicate more personally with audiences.

The process of behavioral targeting

The data collection process

User data can come from several different sources. Depending on the source, there are many different ways to collect data. For website behavior, a pixel is used. This process creates and updates cookies that understand how the user interacts with the site. Apps have a similar process. SDKs can collect other behavioral information, such as location data.

This data is usually stored in a DMP, but there are other adtech solutions for storing this information.

Organization and segmentation

Once this behavioral information exists in a central location, the next step is to sort individual users into groups that share the same behaviors.

This segmentation varies significantly depending on the company, product, or goals. For example:

• Potential customers that go to the gym
• Visits gym location 2 times a month
• Current customers who like meat
• In CRM and visited meat weekly delivery page
• Users who are interested in SEO (maybe even more specific, like a this one, this Bristol SEO agency, or even a industry specific one like this one)
• Existing customer who have read at least one blog post related to SEO trends 2020

Delivery and application of behavioral targeting in advertising campaigns

Specific ad campaigns are delivered to match each segment. This process makes the advertising more relevant for each segment and increasing the chance of engagement and boosting conversions.

Activating behavioral targeting

All of this behavioral data can be used across multiple campaigns and in different advertising channels. That’s the benefit of having a centralized place to store the data.

There are multiple ways to activate this data to create behavioral-based ad campaigns that deliver. Here are some examples of how to enable behavioral targeting to drive engagement and increase conversions.

Examples of behavioral targeting

Cross-selling and upselling

Knowing what your customers like and understanding how they interact with your business is a powerful way of knowing which additional products to promote to them. If you can link product A and B, then your audience that has shown interest in product A that are likely to engage with a campaign promoting product B.

Behavioral targeting in targeted email campaigns

That’s right, and behavioral targeted email campaigns doesn’t just sit in the world of programmatic media advertising. Creating personalized email campaigns based on how your audience is using your site or app is a great way to start.

Examples include targeting cart abandonment sessions, including viewed products in routine updates or directly linking content related to what your audiences have already read rather than generic content. Behavioral targeted email campaigns is a powerful way to increase email productivity and boost your targeting options.

Remarketing with behavioral targeting

An advantageous and accessible way of using behavioral targeting is to retarget. By identifying users that visit your site, you can reach them on other websites to encourage them to visit again and complete goals.

The most common solutions for this are facebook and google as they have simple to install tracking pixels that can understand users that visit specific pages on your site. You can then activate these segments directly in their platforms.

Location-based targeting

Location-based targeting is an excellent way of reaching audiences based on their real-world behavior. You can retarget audiences that have visited your physical stores, or a competitive store. This can also be applied to e-commerce and other online stores.

These targeting campaigns can be useful because the insights are related to how consumers behave in the real-world. This allows you to create compelling segments based on how people behave over time.

James Ewen

James is the head of marketing at Tamoco

Online programmatic advertising is a huge, multi-billion dollar per year industry. Ad spend in this area is expected to reach over $300 billion next year. As well as this, other forms of online advertising are expecting similar growth.

The ease of programmatic ad buying and the vast growth of the market has lead to a rise in ad fraud that has infected the advertising ecosystem. Some estimates state that up to $42 billion will be wasted in 2019 due to fraudulent ads.

Some measures have been taken to protect against some basic types of ad fraud. But to counter more sophisticated fraud, advertisers need a more robust solution to counter the huge amount of ad fraud that exists in the industry.

Location could be this solution. Understanding device location and historical behavior can help to identify fraud better than other methods. In this post, we’ll look at the ways that advertisers can use location data to reduce ad fraud and limit the damage from malicious actors in the advertising ecosystem.

Eliminating ad fraud with location

Does the device exist?

The first step is to identify if the device is a real device and not an emulator. Emulating a device is a common way of faking ad impressions and clicks. In some cases, emulators can even generate IP addresses to pass as a real device.

In this case, location needs to be more precise; the ad inventory needs to combine with sensors to verify that the device exists.

Are the ads landing where intended?

Let’s say that you have a campaign running in the US, and you are only targeting devices in the US. You can use location data to map where the ads are being delivered to the device. If there is a considerable disparity between targeting and delivery, then it’s highly likely that some of your campaign inventory is fraudulent.

Identifying fraudulent inventory is essential as often devices can change or move, and the targeting solution will not update these. But other times, audiences can contain bad inventory, deliberately including devices that don’t meet the criteria. This is why you should always carefully vet your data and audience providers.

Countering smarter ad fraud

What about eliminating the more intelligent fraud? Some ad fraudsters are generating fake IP addresses to spoof IP location monitoring.

Using a powerful location SDK can eliminate this. An SDK uses many signals to identify device location with greater accuracy correctly. Subsequently to trick a location SDK into registering a click in a fake location is much harder to do than a simple IP trick.

What about click farming?

In some cases, fraudsters will pay a real person to click and interact with specific ads in several different locations. Sometimes these devices are kept in one place; other times, they are the person’s personal device.

Location data associated with a device can be used to see if the device moves and behaves like a regular device. Understanding if a device stays in one place and combining this with other fraud detection methods, such as time to install, can dramatically increase the identification of ad fraud.

Towards a version of location ad fraud detection.

Integrating precise location into your ad stack can have a substantial positive impact on your ability to detect ad fraud. But using location data in a more traditional way can also help to understand if clicks and conversions are being bought.

For example, location-based attribution is the process of measuring if an exposed device eventually visits a physical location. This can also act as a way of vetting audiences and inventory.

Location data has many powerful applications across the advertising ecosystem. Detecting ad fraud is another application that allows advertisers and marketers to use location to reduce wasted budgets and identify partners that may be supplying them fraudulent inventory.

James Ewen

James is the head of marketing at Tamoco

If there is a ‘silver bullet’ to marketing, it would be data. 

Data is the raw material marketers need to make sense of things so that they can do their job with precision and purpose. There’s a million marketing tools and templates available on platforms such as Notion, but this understanding is what empowers marketers to understand their customers, based on the actions they take, revealing their most authentic intentions.

In a recent survey, 40% of brands plan to expand their data-driven marketing budgets, while 88% of marketers used data to enhance their understanding of the customer. Quite clearly, data is slowly becoming to marketers; what oxygen is to humans.

In this article, we’ll look into how data is revolutionizing the world of marketing. If you’re a marketer, you’ll get some robust insights into how data-driven marketing is shaping the future of your profession. So let’s get into it!

Personalization Of Marketing Campaigns 

Imagine being greeted by your first name the second you visit a website. Or receiving an email addressed to your name with a list of your favorite products. Better yet, being notified about ordering your groceries every week with personalized recipe recommendations. Are you impressed yet?

That’s precisely what data-driven marketing enables you to do. By collecting critical pieces of data about customers at various marketing touchpoints, like their name, contact details, what they’re interested in, what they’d like to hear about and who they want to hear from, marketers are empowered to be strategic in all their campaigns.

Amazon, for instance, uses customer data to analyze their historical purchases to show them product recommendations based on their shopping habits. They’re able to showcase customized product pages to appeal to customer interests, so they’re more likely to buy. These customized product pages could include customized product recommendations, and even personalized pricing to induce customers to buy.

Capitalizing on customer data is excellent for both customers who receive personalized communications, and marketers, who make a positive impact on the bottom line!

Predictive Analytics

HIstorical customer behavior is one of the best ways to predict how customers are likely to behave in the future. For instance, if you’re a grocery store, and a customer has always been health conscious his whole life, ordering sugar free granola bars for the last three years, the chances are that he is going to continue ordering them from you in the near future.

When customer purchases become predictable, businesses can capitalize on this information by ‘automating’ their sales. Essentially, they’d offer the customer a chance to make ‘repeat purchases’ based on the predictability of their shopping behavior.

Building on the Amazon example, they’ve recently obtained a patent on a system called “predictive dispatch” to send products to customers even before they buy it! This is a real game-changer for Amazon, and it’s customers. Amazon can stabilize their revenue, and customers purchase products without having to put any effort into actually making the purchase.

And with the rise of tools that can help access public data, it’s easier to say “what is web scraping, and how can this provide data that will boost my marketing”.

Customer Segmentation

Customer segmentation is the act of ‘clustering’ customers into groups to identify unusual patterns. For instance, your data may reveal that customers from a particular city are more likely to buy your products than others. Or you may discover that customers belonging to a specific age demographic purchase different products from you when compared to other age groups.

Tools like Tamoco can be extremely useful to gather location data to help you segment your target audience. For example, Tamoco collects information based on location to further segment your audience based on specific interests, how many times they’ve visited a location, common preferences, and demographics including age, gender, and even home and work location.

These insights can be golden opportunities for marketers to create bold campaigns that optimize their return on investment. By clustering customers into specific groups, they can create separate marketing campaigns for each segment, making their content highly relevant.

While there are several techniques marketers use to segment data, the overarching goal is to identify anything of interest that helps them boost revenue and meet their goals. With effective customer segmentation, marketers can:

• Identify who their most profitable and least profitable customers are.
• Predict future customer patterns.
• Improve their marketing focus by creating relevant content.
• Build loyal relationships.
• Price products differently.
• Develop better products based on customer interests.

Inevitably, high-quality data is the precursor to doing segmentation well. That’s why businesses must continue to invest in collecting high-quality data so that all segmentation efforts can be fruitful.

Optimized Paid Campaigns

By collecting data about customers, social media platforms like Facebook and Linkedin make it possible for marketers to customize paid ad campaigns, at scale. What this means is that they can create separate ad campaigns for specific groups of prospects, for paid campaign success.

Additionally, big data makes it possible for marketers to conduct “remarketing” campaigns. Remarketing campaigns are ads that literally ‘follow’ your customers online, wherever they browse, once they’ve visited your website.

Chasing customers online with your paid ads can be an effective strategy when executed well. As per the ‘rule of 7’ in marketing, a prospect needs to be exposed to your ad for a minimum of 7 times before they decide to take action on it.

That’s why some marketers are looking to focus on specific platforms, such as LinkedIn marketing.

While big data makes it possible to chase customers with paid ads, it’s important not to make your customers feel stalked when creating remarketing campaigns. You should endeavor to expose your ads to customers by spacing out the time of exposure, so your ads appear more natural, and don’t come across as being pushed onto prospects!

Your Business Size Doesn’t Matter Anymore

Whether you’re a big business with over 500 employees, or a small business with under five employees making category specific products like an underwire bikini top, software tools make big data easily accessible to all. That’s the beauty of marketing on the internet!

You can be just as effective at marketing no matter what size business you are, because success in this game is dependent on how well you utilize the data to your advantage. While the size of your marketing budgets may certainly have a role to play in the extent of your success, you can still achieve a high degree of precision in your marketing campaigns and acquire customers rapidly, with big data being your marketing backbone.

Free online tools like Google Analytics have made it possible to collect and analyze big data in real-time. Small businesses need not spend money on buying expensive tools to get a deeper understanding of who their customers are since google makes it easily affordable. Before the ‘big data era,’ this was impossible to do.

Wrapping It Up

Big data makes the future of marketing very bright! With high-quality data being collected in real-time, and the availability of technologies like machine learning and AI, the world of marketing is up for massive changes. It’s no surprise that only the sky’s the limit to what sophisticated marketers can achieve in the near future!

Ryan Gould

Vice President of Strategy and Marketing Services

Elevation Marketing

From legacy Fortune 100 institutions to inventive start-ups, Ryan brings extensive experience with a wide range of B2B clients. He skillfully architects and manages the delivery of integrated marketing programs, and believes strongly in strategy, not just tactics, that effectively align sales and marketing teams within organizations

Ryan Gould

www.elevationb2b.com/

What is the bidstream?

The bidstream is a network of advertising requests that deliver ads to mobile devices.

A bid request refers to the moment when a publisher auctions off an ad slot to an advertiser. This request delivers an ad to the device.

When the ad is delivered, some information is passed back the other way. This information contains ad related information, but ofter it comes with additional details. These sometimes include a form of location.

This location data is then packaged and used for a wide range of applications.

But sadly this isn’t always a great proposition. Here’s the thing with your bidstream data…

The problem

Geodata is no longer just an experimental solution. Location data is fueling some of the most advanced marketing efforts.

Because of this, marketers are rightfully demanding greater transparency around this data, where it comes from and how it is created.

The problem with bidstream data is that it is often inconclusive, inaccurate, or even fraudulent.

The thing with bid stream is that it can very quickly provide a large amount of scale. Due to the sheer number of devices that display ads, the number of location points can be quite appealing.

However, too many marketers are blinded by this scale and refuse to focus on data quality.

This quality is what provides lasting ROI for marketers and allows for effective targeting, attribution, and insights.

The common pitfalls with bidstream data

General precision issues

Not all bidstream data is inaccurate but the data is often imprecise. What’s the difference? Well, it comes down the detail of the device location.

Some bidstream data is based on the IP address of the device. Sometimes this can cross over an area as large as 1km. In a city, this is not precise enough to understand the context of the device.

bidstream data that is collected in this way doesn’t go far enough to understand the context around device moment. SDK based data, for example, can understand the difference between a device walking past a store and a device visiting a store for a coffee.

Cached IP address

A common issue with bidstream data is that the device often passes back cached location signals. If a device has connected to a network before it can sometimes deliver this cached address, even when the device has moved to a new location.

Teleporting

Bidstream data is often confusing if you sit down and analyze it down to a device level. For example, we’ve seen devices move across the world in a matter of minutes!

This disparity demonstrates the issues that bidstream can present for marketers. The use of a VPN can cause these discrepancies.

These factors mean that bidstream data is unreliable. Some reports have places accuracy levels of bidstream data at less than 10%.

Marketers may be able to get their hands on large quantities of data through the bidstream, but this data has to be rigorously filtered to ensure any level of accuracy. Even then, these levels of accuracy are often unsuitable to carry out the type of campaign that will produce the desired results.

How do we know this?

We know what good data looks like because we deal with it every day.

We’ve spent years building a dedicated SDK that provides anomynized location data from mobile devices.

It’s the product of years of focusing on the inaccuracies involved in device location, and we’ve built many solutions to identify location data that is both precise and accurate.

But here’s the kicker – we thought about scale as well. We released that advertisers needed a way to scale this data to satisfy their marketing goals.

That’s why we worked on deploying our SDK to compete with the scale of bidstream.

Conclusions

Location data comes in many forms, and each has its advantages and disadvantages. Transparency is key, and marketers should understand that the data they use in their campaigns should be rigorously tested for accuracy.

The bidstream can generate large amounts of location data instantly. This data is often inaccurate and imprecise.

SDK driven data collection offers much-needed improvements in data accuracy and allows marketers to execute better campaigns.

James Ewen

James is the head of marketing at Tamoco