Inhouse Data Management Platform – Visualization

Challenge & Selection

I used the Visualization tool to get help with Visual Thinking, for understanding the benefits of having an  inhouse developed and owned Data Management Platform and to identify and define possible  challenges that we could get over just by having a unique data as being a mobile network operator. I use  this technique with my upper management to convince them to invest on a long term platform,  including development and data fine tuning tasks, which are heavy effort for any company that has this  size of data and number of customers. Thus, the position of a DMP in digital advertising ecosystem is  very critical for the future of this business.

Application

First of all, every stakeholder should align on, where does DMP fit in all digital advertising ecosystem,  from advertisers, to agencies, to adplatforms (DSP and SSPs) and publihers.. While big data is  instrumental to effective data-driven marketing campaigns, you can’t do much with the raw  information. You need it sorted and converted into a usable form, at least so you can understand what  you’re looking at. This is the power of a DMP.

A DMP collects and organizes data from a variety first-, second- and third-party data sources, and makes  it available to other platforms such as DSPs, SSPs, and ad exchanges to be used for targeted advertising,  personalization, content customization and beyond. Some people describe a data management platform  as the “pipes” of ad tech — connecting many platforms in a neutral way so marketers can use their  powerful audience data when and where they want.

This first-party data — that is the data you own and have collected directly from your own customers —  can be collected based on specific behaviors such as clicks, downloads, video uploads or video  completions, interests like sports, football, parenting, museums and travel or demographic information.  It can also include demographic data, socio-economic data, influencer and action data. As an example, a  business can use a DMP to collect and organize data, then use that data to target a particular ad to  moms who are 25-35, there are endless applications of a DMP.

Once the first-party data is collected, it is organized into a series of segments called a “hierarchy”, which  can change based on each end user’s business models. A large publisher network may have their  hierarchy divided up into different buckets based on each of the individual websites they own. An  agency can have separate accounts for each of their advertiser clients. Marketers could manage  different brands’ data separately, while also having an overall holistic view of the data at the top level.

If appropriate to the situation, then I will create a visual, either based on a high-level process flow with  swim lanes for different stakeholders, or another format.

The final step is to activate the data, by putting it to work! This activation step relies on the DMP having  integrations and open APIs with other platforms, so that the audiences you build in the DMP can be  seamlessly transported to DSPs, SSPs, and beyond. The most common DMP use case is running a  targeted campaign to a specific audience via a DSP. Or, you can connect the DMP to your content  management system (CMS) to adjust the content of your website for certain audience groups. The  possibilities and use cases for data activation with a DMP are limitless.

Insight & Approach

What I have learned from conducting this exercise with several groups is that once we’ve collected and  organized our data, it’s time to build unique audiences in DMP so we can identify most valuable  segments and use them across any digital channel. For any particular targeted campaign, a marketer can  predefine the target audience for that campaign based on data gathered from your DMP audience. So  instead of choosing to spend your advertising dollars on a particular financial website to reach an  audience of folks interested in finance, you can instead build a financial audience based on actual  behaviors across the wider Internet.

Audiences can be built inside the data management platform using any combination of first-, second-  and third-party data sources, which are combined using Boolean logic, which breaks down all values into  either true or false. You can build as niche an audience as you wish, and are only really limited by the  scale you need. Generally, the more niche the audience, the smaller the size.


Inhouse Data Management Platform – Visualization Challenge & Selection I used the Visualization tool to get help with Visual Thinking , for understanding the benefits of having an inhouse developed and owned Data Management Platform and to identify and define possible challenges that we could get over just by having a unique data as being a mobile network operator . I use this technique with my upper management to convince them to invest on a long term platform , including development and data fine tuning tasks , which are heavy effort for any company that has this size of data and number of customers . Thus , the position of a DMP in digital advertising ecosystem is very critical for the future of this business . Application First of all , every stakeholder should align on , where does DMP fit in all digital advertising ecosystem , from advertisers , to agencies , to adplatforms ( DSP and SSPs ) and publihers .. While big data is instrumental to effective data - driven marketing campaigns , you ca n’t do much with the raw information . You need it sorted and converted into a usable form , at least so you can understand what you ’re looking at . This is the power of a DMP . A DMP collects and organizes data from a variety first- , second- and third - party data sources , and makes it available to other platforms such as DSPs , SSPs , and ad exchanges to be used for targeted advertising , personalization , content customization and beyond . Some people describe a data management platform as the “ pipes ” of ad tech — connecting many platforms in a neutral way so marketers can use their powerful audience data when and where they want . This first - party data — that is the data you own and have collected directly from your own customers — can be collected based on specific behaviors such as clicks , downloads , video uploads or video completions , interests like sports , football , parenting , museums and travel or demographic information . It can also include demographic data , socio - economic data , influencer and action data . As an example , a business can use a DMP to collect and organize data , then use that data to target a particular ad to moms who are 25 - 35 , there are endless applications of a DMP . Once the first - party data is collected , it is organized into a series of segments called a “ hierarchy ” , which can change based on each end user ’s business models . A large publisher network may have their hierarchy divided up into different buckets based on each of the individual websites they own . An agency can have separate accounts for each of their advertiser clients . Marketers could manage different brands ’ data separately , while also having an overall holistic view of the data at the top level . If appropriate to the situation , then I will create a visual , either based on a high - level process flow with swim lanes for different stakeholders , or another format . The final step is to activate the data , by putting it to work ! This activation step relies on the DMP having integrations and open APIs with other platforms , so that the audiences you build in the DMP can be seamlessly transported to DSPs , SSPs , and beyond . The most common DMP use case is running a targeted campaign to a specific audience via a DSP . Or , you can connect the DMP to your content management system ( CMS ) to adjust the content of your website for certain audience groups . The possibilities and use cases for data activation with a DMP are limitless . Insight & Approach What I have learned from conducting this exercise with several groups is that once we ’ve collected and organized our data , it ’s time to build unique audiences in DMP so we can identify most valuable segments and use them across any digital channel . For any particular targeted campaign , a marketer can predefine the target audience for that campaign based on data gathered from your DMP audience . So instead of choosing to spend your advertising dollars on a particular financial website to reach an audience of folks interested in finance , you can instead build a financial audience based on actual behaviors across the wider Internet . Audiences can be built inside the data management platform using any combination of first- , second- and third - party data sources , which are combined using Boolean logic , which breaks down all values into either true or false . You can build as niche an audience as you wish , and are only really limited by the scale you need . Generally , the more niche the audience , the smaller the size .