Big data in 2013: dynamic budget allocation and the right business intelligence solution bring performance
The data generated globally every day is estimated at about 2.5 trillion bytes, which means that the total data volume doubles about every one and a half years. Technology is developing as fast as the amount of data is growing, thus, modern marketing solutions are able to measure and collect an incredible variety of customer and viewer information. Ad server, tracking, targeting and CRM data is what‘s important for digital performance marketing, but location-based data, weather data, social, demographic and user behavior data are of interest for analysis as well. As always, the goals are to use marketing budgets in the most efficient manner and to increase ROI.
Here are some useful tips to get in control and make the most of the huge amounts of data available in 2013:
1. Make sure your data is usable
In order to extract useful information from big data, the data must be accessible and analyzable in the first place. Consequently, marketing and IT will need to cooperate well, so that modern business intelligence solutions are able to analyze and depict data from many sources. The more data you can effectively make use of, the better the effect on the ROI. You can even include budget data and analyze the efficiency of your efforts.
2. Agencies and software providers
Are you still employing a separate agency for each channel? To make the best of big data this might be a mistake. It is better and more efficient to use one provider to analyze and optimize all the data from all the channels. This chosen provider will have a more holistic view of the data and the company and probably even uncover weak points or possible synergies.
3. Define your attribution model
How are you planning on investing in performance campaigns? Are advertising contacts in the middle part of the buying cycle of importance? Is it the last click, or the initial ad view which contributes most to the success of a campaign? Before you get started with big data, you need to define what kind of attribution model fits your campaign and your product best. After that you can optimize. By the way, this is also what you need for an efficient bidding strategy in real time bidding.
4. Budget allocation
Data analysis has proven this again and again: it’s a mistake - in most cases – to allocate budgets based on the last cookie. Campaigns on different channels influence each other and invest in each other. Of course, you need to handle strong affiliate partners with care, but in the long term you need to rethink in terms of which role the last data cookie is playing. This renewal of processes should be based on a detailed customer journey analysis. The trend in 2013 will go in the direction of dynamic budget allocation.
5. Centralize Data
Whether you are collecting data from campaigns, website tracking, customer journey analysis, or budget information: all data related to online marketing, which is collected from a large variety of sources, should be fed into one central system and be analyzed there. Ad server functionalities by themselves are not going to be enough. Only innovative business intelligence (BI) solutions will identify the correlation between investments put into a display campaign and the total CPO of a performance initiative. Intelligent tools with real time monitoring will display the success of a campaign, making use of predefined KPIs.
6. Think ahead
Refined analysis is not enough. Forecasts are important as well. When choosing a business intelligence solution, make sure you pay attention that it is not just able to process and analyze all available data, but rather can also generate forecasts. Partial solutions will just waste your money - thus, make sure that the solution you choose will provide graphic material to assist you in making the right decisions.
7. Use your own data
Incredible amounts of data are available these days, but not used efficiently. Before you consider making use of third party data, make use of your own, e.g. from your website. Not only will you avoid data privacy issues, but you will also have highly relevant data. However, don‘t forget to inform your website visitors about the anonymous tracking of the user data.
8. Cookie lifespan
In order to control the "data monster", you will need patience amongst other things. Buying decisions often need several weeks, at times even several months, and you need to consider this when you are collecting customer journey data. Thus, cookie lifespan might need to be adjusted - for example, in the travel sector.
9. Consistent tracking, detailed targeting
Targeting can get more detailed the more data you have. You might suffer some losses in regard to reach, but better conversions will more than make up for this. Adjust your advertising material to cater to buying habits, interests, and intentions of potential customers, and this will push your performance marketing.
10. Make use of social
Data from the social web is an important part of big data. Community management, marketing, product development, public relations and sales - they all will profit. It is important to monitor the social web with the right software solution to extract people’s opinions about your brand, your products and your campaigns. Analyzing this data can be valuable for planning future campaigns. If your existing customers are using their real names on the social web, you can even augment your customer profiles with data collected from social.
If you make proper use of big data, it will act as a conversion catalyst, so what are you waiting for?
By Anjum Siddiqi