- Data Stream - what types of data does it include?
- How to use Data Stream in practice?
Data Stream is a feed of information, which can be provided on dedicated platforms, such as Data Management Platform (DMP). It contains raw data that is based on the user’s browser behavior. This data can be used as a good source material for building your own data tools, preparing Big Data analysis to improve your product or to making a research before a new product release.
Data Stream – what types of data does it include?
By using Data Stream, you collect all the data via pixel implemented inside the website’s source code. IDs of used data points and segments may be stored on DMP and then can be combined with supplying data from Data Stream, which contains, for example, timestamp, number of occurrences or cookie lifetime.
Data Stream can be used to observe users’ behavior and compare their characteristics, watch their interests and intentions, and predict future actions. To learn more about this service, check one of our posts: “What is Data Stream?”
How to use Data Stream in practice?
There are loads of possibilities to use raw data in digital environment. Data scientist can modify digital information to build new tools or upgrade current ones. Below we gathered 5 ways most popular and efficient ways to use Data Stream in your company or agency:
1. Personalization of advertising campaign
Data Stream delivers detailed characteristics of websites’ visitors that allow observing their browser behavior. Collected data can include specific buying intentions or general interests, age, gender, and location. Thanks to this information marketers are able to personalize their campaign by taking into account current needs of their target audience.
Example: users who show intentions to buy a car can be targeted by a bank that offers car credits.
What result it gives: Data Stream as a source of insights gives an opportunity to increase conversion rate of dedicated ad campaigns.
2. CRM Enrichment
Companies base their campaign on data from integrated analytical systems or CRMs. Using cookie matching process, Data Stream enriches user profiles with certain characteristics of online behavior. Companies which decided to enrich their client bases with Data Stream, have data benefits in following scopes:
- interests
- buying intentions
- demography
- given brand search
Additionally, Data Stream provides details about number of occurrences of certain event and timestamp up to milliseconds.
What result it gives: increasing the effectiveness of sales communication with a personalized message for your customers.
3. Users profiling
Data Stream service can be used if marketer would like to base a campaign not only on the latest user click before conversion but on actual path that has been passed by the user before conversion. It would be enough to focus on 1st party data (for example, from online ads, main page, landing page) and track the parts that user had a deal with before he made a purchase or filled the form. Such actions allow defining a part of marketing funnel, where user had a contact with the brand.
Example: AIDA (Attention, Interest, Desire, Action) is one of the oldest marketing models. It depends on 4 basic steps which being correctly set, provide to the 100% conversion. In a few words, marketer needs to attract attention to their product, then bring interest to it (e.g., present benefits of using it), cause a desire to have it and call to action. On each of the mentioned 4 stages, user has contact with brand before the actual conversion. Data Stream delivers this exact information too.
What result it gives: Company consciously builds their own strategy of online communication, knowing which marketing channel to choose during each stage. Presenting of “Customer Journey” is also an identification of the most successful marketing channel within communication with customers.
4. Effective remarketing
Marketers are able to direct the media budget to the specific users’ group based on given criteria. Data Stream helps to differentiate users and target those, who had visited their website, but didn’t make a conversion. Their behavior still telegraph buying intentions – by searching the same subject on the internet.
Example: Travel agency targets users who didn’t buy a trip on their website, and still are looking for other options on the internet. Thanks to this data, agency makes retargeting of audience that represents a chance for conversion.
What result it gives: Data Stream usage allows saving more than 30% of the total ad budget, with conversion rate being kept.
5. Detection of bot traffic
Delivered by OnAudience.com raw data contains information about the cookie lifetime in our ecosystem. If a cookie was used just once without any history being kept, this means that the cookie was rather created by a bot. Raw data also identifies time, when a certain event occurred. For example, if two events occurred in a very small time interval between each other, this also suggests that the traffic is generated by bots.
Example: a timestamp as a part of Data Stream is written in UTM time format, e.g. 2019-02-26T12:51:19.000Z. This particular time represents date February 26, 2019 and 12:51:19 as a time of event.
What result it gives: ad budget is being used for real users instead of bots.
Data Stream is a powerful tool in Big data field, with global privacy data regulations being kept and quality-assured. OnAudience.com Data Stream includes high-quality information and it is fairly enough for targeting purposes, finding valuable insights about online users’ behavior or improving business analysis.
