Credit card companies can analyze consumer purchases to identify the use of stolen credit cards, but they are able to use the same insights to predict divorces.
- Robust marketing personalization capability offer marketers the insights needed to increase their customer acquisition and retention rates.
- By improving the granularity of data in these systems, you can improve the accuracy of predictions. But you can also easily cross the data privacy line.
This article not only explores the tension between accuracy and privacy, but also offers marketers concrete ideas.
How anonymous is the data in marketing systems?
Marketing personalization technology enables marketers to build a better profile of their customers by analyzing what they are browsing, where are they coming from, what they are purchasing etc. Thy use this information to raise conversion rates and increase share of the wallet. Similarly offline businesses such as Walmart and Kohl’s analyze sales, pricing and economic, demographic and weather data to tailor product selections at particular stores and determine the timing of price markdowns.
As the amount of customer behavior data available skyrockets and analytic methods become more sophisticated, opportunities of a new order of magnitude become available to those who take advantage of it. The value and quality of these insights increases with the specificity of data. However, every time data gets filtered, its analytic value diminishes. Thus, businesses that want to increase the reliability of their predictive conclusions often seek to maintain and use as many dimensions of the data as possible to keep it more specific, rather than filtering it.
The general consensus is that marketing personalization solutions use aggregated data. However the aggregated data is not as anonymous as perceived. If one anonymized data set was combined with another completely separate data base, it is possible individuals could be re-identified. Armed with bits of information about me from such databases, my profile can be accurately pieced together. Some retailers have used these insights to predict such intimate personal details such as if the baby is on the way (as early as in their second trimester).
The constant battle between privacy and accuracy
Businesses view their personalization systems as infinitely growing repositories; the bigger the repository, better the quality of insights. However they can easily cross into the realm of data privacy. Hence businesses that want to aggregate data from various sources must often comply with data privacy rules. Balancing data insights with data privacy issues becomes important.
Privacy is a relative term
There are country-specific laws governing the collection and usage of data, let alone protecting a global citizen’s right to privacy. Governments and regulatory agencies have drafted a wide range of data privacy rules, regulations, laws, directives and frameworks in an effort to address the concerns data use creates. These include the EU Data Protection Directive, the APEC Framework etc.
Privacy and security – two sides of the same coin
Privacy is not the only issue that needs to be addressed. Businesses need to also adhere to the clearer guidelines on corporate data preservation duties. Policies that allow too much data to accumulate (which marketers want) may increase the cost of future, unanticipated litigation. Conversely, failure to retain enough data may lead to accusations of spoliation.
As our data is shared with third parties it also raises an interesting question as to what data is being shared specifically and how that information is being secured by these third parties. If there were a data breach by one of these parties and this information fell into the wrong hands, it could it be used for malicious intent.
As a marketer, following are the five steps you need to take as you seek a balance between the three elements: growth of your marketing personalization capability, data privacy and data retention.
- Comply with country-specific or region-specific data protection policies.
- Develop clearly defined data retention policies
- Ensure the data collected does not directly violate privacy and retention policies.
- Put mechanisms in place to secure the data, so it cannot be stolen
Siddharth Taparia (@siddharth31) is Vice President of Marketing at SAP.