Tag: Segmentation

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Data Marketing & Advertising

Using Location Audience Segmentation Directly In Your DMP

Audience segmentation

Why location is important

Advertisers use audience segmentation so that they can eliminate any unnecessary spend from their marketing efforts, become more efficient and effective and boost key KPIs.

Using data, advertisers can create much smarter audience segments. They can prioritise the right consumer, with the right ad using the right message.

That’s why we’ve made sure that our precise, first-party data sets are available for marketers and advertisers to use directly in their DMP. Advertisers should be able to do this directly in their media buying solution.

 

About our data

At Tamoco we think that data accuracy is the most important thing for advertisers using data in their targeting, segmentation or attribution. That’s why we built a network that is leading the way in the drive towards more accurate data.

 

Proprietary location data focused on precision and accuracy

Tamoco’s data is industry leading. We use our proprietary SDK for data collection along with our extensive network of sensors to understand consumer location with higher levels of precision and accuracy.

 

Detailed visit behaviour

Tamoco’s data methodology is designed to reduce the number of incorrect data points. We understand visits with granular accuracy. False visits are filtered out, and our data methodology is transparent. This methodology means that advertisers can be confident that Tamoco visits data is more accurate than other visits-based targeting solution.

 

Benefits of using location directly in your DMP audience segmentation

Fine-tune audiences and incremental ROI gains

You have the first-party data which contains, for example, age, gender, brand loyalty and products owned, amongst others. Location allows you to segment these audiences even further.

To drive incremental gains to ROI location can signify which of these users are relevant to your campaigns. Location data is real-time and behavioural based. These attributes mean that you can exclude irrelevant audiences, and save valuable marketing dollars in the process.

Advertisers can then tailor their campaigns to users that have physically exhibited certain behaviours, such as visited a specific store or frequented a series of physical locations.

This targeting helps to build relevant messaging and ensures that your segments are squeaky clean in terms of precise targeting. No more wasted budget on consumers that aren’t relevant to your brand campaigns.

 

Location is a good indicator of intent

Add intent to the segmentation process. Retargeting campaigns are more effective if you can reach consumers when they are in the right frame of mind. Retargeting works well in the online world, but this is often limited to your current inventory.

Consumers show purchase intent in the offline world as well. Visiting your store is a good example. However, by mapping the offline world, advertisers can use location to identify consumer intent in different ways.

Retargeting to consumers who have visited (or are currently visiting) a competitor or a store in a similar category is a powerful way to reach the right audiences.

 

Using location data to fuel analytics

Using location signals directly in your data management platform enables smarter cross-selling. If you have built up a database of descriptive and behavioural audiences, adding location can provide a better way to upsell new products or promote return purchases.

Using your analytics solution, location data can directly increase how you understand consumer trends, patterns and intent. Location data is a tool for building up a more detailed view of your customers.

These insights can be used to inform future segmentation and predict which audiences are more likely to convert at a specific stage in the buyer journey.

 

Using location to build lookalike audiences

Reaching new customers that are currently outside of your customer data set can be challenging. It’s something hard to know if the process of building lookalike audiences is reliable.

Using location data, it’s possible to build real-world behavioural based audience segments. For example, by taking an audience that converts highly, we can understand similar consumers based on how they move and behave in the real world.

This generates lookalike segments that are based on current real-world behaviour rather than vague similar interest data. Ultimately it will build segments that are more likely to convert.

 

Example segments and audience segmentation strategies

Some of our location-based segments are available already. Here we will look at some familiar audiences segmentation use cases using this data.

 

Women’s clothing stores

Brands looking at segmenting their audiences based on consumer interests can use location to refine their audiences. Let’s look at how this would work with an audience based segment.

You already have a pre-built audience that is relevant to your women’s clothing brand.

Using location-based filters directly in your DMP you can further filter this audience to reach the most relevant users.

You can filter based on the number of visits to women’s clothing stores. You can set the time period for these visits.

This will segment your audience based on those that have physically visited a clothing store in your defined time period.

 

Drinking places (alcoholic)

Using location, you can build retargeting audiences in your DMP to maximise your ad budgets.

If you are looking to retarget consumers based on their behaviour, then location can help to define the right audience.

Set your audience to include those that have visited an alcoholic drinking place.

You can filter these visits based on past visits, or on specific dates or days of the week.

This can help you to build incredibly specific audiences – such as Friday night venue attendees.

 

Speciality food stores

As previously mentioned, location data can be helpful to build new lookalike audiences based on consumer behaviour. This method can help you to create unique lookalikes based on actual measured real-world behaviour.

We can build an audience based on visits to speciality food stores. Here we have our seed audiences that consists of consumers that we know have visited a health store at some point in our defined time period.

We can do one of two things here:

  • Move the identifiers into our current lookalike modelling solution. This will create a new audience based on a unique seed audience.
  • Use a location-based lookalike solution. This will use the audience to match with devices that have exhibited similar real-world behaviour.

All of the above segments are readily available in leading DMPs and other media buying solutions.

 

How to activate Tamoco’s precise location data

Our data is currently available through DoubleClick, AppNexus, AdForm. Here you can begin segmentation immediately using Tamoco’s location data.

We can activate these segments instantly in The Trade Desk, Adobe Marketing Cloud, Facebook Advertising, Sizmek, Beeswax, Widespace and BrightRoll. Please contact us to enable this.

 

Want something more custom?

We can build custom segments on demand with our team of data scientists. These can be fed into the above solutions. Here are some examples of what our team can provide for your campaigns.

Brand affinity – we can create segments that are based upon brand affinity to your brand, a competitor or another relevant brand.

Detailed visits – Our team can help segment audiences based on verified visits to any physical POI, venue or location.

All of our data solutions can be fed into your current data or targeting platform. Our team of data scientists are ready to support your integration and take your marketing to the next level.

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Get in touch to learn more

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Categories
Marketing & Advertising

Mobile Targeting – Get Programmatic & Social Right With Data

There have been issues with data accuracy in mobile targeting in the past. Targeting the right person in the best moment is still the appropriate goal for marketers. But to do this effectively, the data that fuels campaigns must be reliable.

If marketers don’t work from reliable data sets then the information is useless, and mobile targeting will be more of the same.

Today, the availability of scalable first-party data sets is there. Brands and advertisers need to be able to understand what good data should look like.

We’ll look at a few fundamentals to look for that will ensure your mobile targeting campaigns are powered by quality data. We’ll also discuss the effect this will have on different mobile targeting channels.

 

What is quality location data?

When we talk about data we look for the following attributes:

  • First-party – is the data from a first party source. Second-hand data that is unverifiable is not helpful as it could be inaccurate or out of date.
  • Sensor-driven – this means that the data sets are sourced from accurate sensors. Precise and reliable data sets are sourced from multiple sensor types to ensure accuracy and scale.
  • Real-time – Datasets must be immediate in order to verify accuracy. To achieve effective personalisation and mobile targeting, action must be taken based on data sets that are real-time.

 

Programmatic advertising & location data

Location is a fantastic trigger to help fuel mobile marketing campaigns. That is if you can get the moment right.

Programmatic has always had its problems – automation is difficult to get right. A lot has been said about programmatic and it’s effect on delivering relevant content to the right person at the right time.

We’ve all seen and remember poor individual use cases of programmatic advertising. Mobile programmatic targeting has taken the plunge and aims to put data at the centre.

However, problems of accuracy remain if the data that is being used to fuel programmatic advertising isn’t accurate.

Location-based marketing and programmatic are effective when the following conditions are met:

  • Mobile targeting can be achieved in real-time
  • Data is derived from accurate, sensor-driven networks
  • The data is first-party

Without this programmatic mobile targeting will be ineffective. Outdated data sets can mean that you completely miss the relevant moment to target audiences.

It can also mean that your attempts to personalize the experience miss the mark. We all know how important personalization is to the modern marketer.

There are a lot of companies that claim to provide accurate data, but these are rarely meeting the three conditions we just discussed.

Often the data is third-party, it’s driven not by accurate sensors, but vague lat/long indicators. It’s often not live or real-time either.

So make sure your data partner can deliver on those three points. This will allow your programmatic mobile targeting to truly feel personal. It’s also important to get a good understanding of what stream processing is.

 

Location-based social media marketing

With organic social media becoming more obsolete, more brands are looking at increasing their ad spend on social to ensure that they reach audiences constantly. One way to do so is by using social media management tools that automate posting regularly on all social channels for maximum reach.

Social targeting options allow for geographic targeting.  But the accuracy of these targeting options is yet to be verified. How do you know you aren’t targeting a user who checked in there over a week ago?

Let’s analyse current social media mobile targeting options in relation to our three commandments.

Real-time – Facebook’s geographical targeting feature is rather vague when talking about its geo-targeting options. Or at least when talking about the speed of the targeting. “people recently in this location” is how they describe it. But there’s little in the way of how recent.

Now, this is useful for some advertisers, but to create a truly personalized and real-time experience, it has to be instant.

Accurate sensor-driven – Again it’s hard to tell exactly how Facebook sources its location data. We suspect that a large proportion of data is derived from check-ins on the Facebook platform. This does raise some issues – it relies on the user selecting the right location, for example.

Social is a powerful channel for targeting users. But the potential is even greater if brands can accurately target users in real-time. It’s even more effective if this is done in relevant locations and with personalized content. This can even be leveraged to create social proof.

In order to achieve that, the data that fuels social targeting and retargeting needs to be accurate.

Social platforms have always focused on personalization of the news feed. But this highlights some of the problems with facebook ads – they aren’t relevant.

Facebook has spent so much time personalizing the organic news feed but then delivers any ad at any time.

This means that brands and advertisers who embark on Instagram marketing can ensure that relevant, in the moment ads, reach users using Instagram stories data will be on to a winning formula.

 

Post mobile targeting attribution

The same can be applied to attribution. Post mobile targeting attribution is valuable for advertisers and marketers. It’s important to measure attribution, especially in the offline world. Mobile location data has been instrumental in this. Closing the online to offline attribution loop is now possible thanks to device location data.

But again, to truly understand physical conversions, marketers need accurate and real-time data sets.

 

Conclusions

Mobile targeting is a powerful tool for marketers to reach users with personalised messages, at the right moment. Location data and location intelligence helps provide the context that mobile targeting takes place.

Whether programmatic or social, mobile targeting requires data. This data must be accurate, real-time and first-party to ensure that location-based mobile marketing is effective.

Precise data is now available at scale. This means that marketers now have a powerful tool at their disposal, as long as they utilize the right data sets.

Categories
Marketing & Advertising

How To Improve Mobile Targeting With Location Data

Mobile advertising is growing incredibly fast. Smartphone adoption has never been higher. Accordingly, marketers are adopting a mobile-first approach. As marketers look to target audiences on mobile devices, they will need to adapt to stay effective at targeting the right person, with the right message at the right time. 

Mobile targeting is set to pass other channels as more budget is being allocated to reaching audiences on the move. To stay ahead here’s how to improve mobile targeting and advertising using location data and today’s location based marketing technology. 

 

Location intelligence is an effective method to improve mobile targeting

Location data is a useful tool to help target mobile devices effectively. It allows in-depth segmentation of mobile audiences. It also facilitates real-time message delivery based on a device’s location.

This level of accurate data insight improves the effectiveness of mobile targeting. Location based marketing has been proven to increase engagement and conversion rates. This is because mobile targeting occurs contextually, at the best possible moment.

Location data is used to build complex mobile audiences profiles. This is achieved by understanding these anonymous location signals. Mobile targeting campaigns should feel personal and relevant to the user.  This is achieved by applying offline behaviour to the targeting process. 

Adding location intelligence to mobile targeting means less chance of delivering content that is irrelevant or annoying. In a world of increased ad-blocking, users want marketing to be helpful. Location based marketing allows mobile targeting campaigns to be just this. They reach users in the best moment with personalized and useful relevancy of the content. 

 

Personalize mobile content and combine this with relevant mobile targeting

Location intelligence allows brands and marketers to target users in real-time with accurate and personalized content. Ensure that mobile campaigns combine accurate targeting with contextual content relevant to the user’s location. Personalization should extend beyond simply addressing a user by name. It should be personalized to a level that reflects the location and situation of the mobile device. 

Personalization is key to successful mobile targeting. Improving the relevancy of the content will improve the success of campaigns. High-level mobile personalization is achieved with accurate location data. Understanding the situation of a mobile user allows content to be targeted and personalised. Users are more likely to interact with content that is targeted to their situation. 

 

Make sure your data is accurate and precise

Using location intelligence to target mobile users in the right micro-moment will improve campaign performance. Targeting devices at exactly the right time ensure that you will reach the user in the best place at the right moment. This requires the location data that fuels your campaign to be precise and instant.

Ensure that your location data partner that can source accurate data in real-time to inform your mobile targeting campaigns. Ask how your data is sourced. Using third-party data may not be helpful as it could be incorrectly sourced or out of date. 

There’s a lot of bad location data out there. Effective mobile targeting should be based on first-party data sourced from precise sensors. For example, at Tamoco, we source location signals across multiple different sensor types. This helps to understand device location with accuracy. It also ensures that errors in location data are not included in data sets. Data is also sourced from first-party sources. This means that there is little chance of data being out of date, or lose accuracy through the reselling of source data. 

Marketers should take accuracy and precision seriously. It means that mobile targeting campaign budgets are as efficient as possible. It ensures that brands and advertisers don’t waste time and money targeting the wrong audience. Each advertising dollar goes further as brands get better, more accurate mobile targeting. 

 

Apply mobile targeting and attribution across channels

Use location intelligence to understand if your mobile targeting is working. Location based marketing provides accurate attribution after devices are targeted. This allows marketers to understand campaign performance in the offline world. The aim of your targeted mobile campaign might be to send users to a specific store. It makes sense to measure the performance of this using location based attribution.

Many mobile marketers aren’t aware of the huge potential for location in closing the online to offline attribution loop. It can help brands to make better mobile targeting decisions over time.

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Discover location based marketing

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