They're watching us...to sell us stuff. (or customer data online.)


Customer information accounts for a huge percentage of big data’s overall makeup. (Christo Petrov, techjury 2019) It’s become standard practice for marketers to use this data to track their performance, which I discussed in my previous post.


But what types of data are online businesses gathering, specifically?


Customer data can be divided under the following categories:

-          Identity Data
-          Descriptive Data
-          Quantitative Data
-          Qualititative Data

Identity data is information which identifies a specific user, such as a full name, their age, their address and phone number or their account information.
Descriptive data adds further detail to identity data, and consists of information about the users lifestyle, career, interests or family.
Quantitative data, or behavioural data, adds context to the customers’ relationships with a company. It consists of transaction information, email and communication preferences, online activity and customer service-related activity.
Qualitative data gives context to customer interactions and transactions. It provides background to customer behaviour, usually gathered through customer satisfaction surveys and NPS activity. This allows companies to understand customer motivation and gain detailed feedback on a product or service.

This data offers marketers a wealth of opportunity, but the use of individuals’ personal information also brings significant challenges as the public becomes less trustful of corporations with their data.

The Benefits of Using Customer Data
By collecting identity and behavioural data about users, marketers have a vast array of demographic information, making it easier than ever to find target audiences for marketing and advertising campaigns. (Nicole Martin, Forbes 2019)

Another key benefit in using customer data is its use in monitoring performance. With so many resources in place to track consumer-brand interaction, businesses can see the results of their marketing efforts much faster than previously possible. (Martin, 2019)

The logical next step in customer data analytics can be found in the developing field of customer journey analytics, or CJA. CJA is an emerging marketing practice which tracks individual customers across all monitored touchpoints, allowing marketers to build a fully realised map of the customers’ “journey” at every stage of their time spent interacting with a brand. (Steve Offsey, Pointillist 2017) 

Using a combination of data types gathered from each stage in the customer journey, companies can gain valuable insight about each touchpoint and make changes where necessary to improve overall customer experience, or CX.

Threats and Challenges to Marketers
As people continue to share more online, the definition of privacy will become less clear. Marketers can access deeply personal information about their customers and must use discretion in the use and security of this data. As online marketing becomes more specific to individual behaviour, public opinion on the collection of personal information is becoming increasingly negative. (Auxier, et al., Pew Research 2019) Recent years have seen multiple, high-volume security breaches at companies like Equifax and Facebook, resulting in millions of individuals’ personal information being stolen. (US Federal Trade Commission, 2020) (Mike Isaac & Sheera Frenkel, The New York Times 2018)

In response to the evident lack of data security online, governments have begun to respond by implementing stricter regulations on data privacy, such as the EU’s 2018 GDPR laws. Businesses must ensure the security of customer data or face heavy litigation. For many small and mid-sized businesses, this security infrastructure is costly to implement and the controls time-consuming. Additionally, smaller businesses are at much greater financial risk than their large counterparts should a breach occur. Marketers must remember to tread with caution in this arena.

At the end of the day, businesses can direct their marketing efforts with never before seen precision, but must always be aware of the risks that accompany the responsibility of handling so much personal information.



SOURCES:
16+ Big Data Statistics - The Information We Generate [2020], 2019. . Tech Jury. URL https://techjury.net/stats-about/big-data-statistics/ (accessed 2.20.20).
Big Data: Forget Volume and Variety, Focus On Velocity [WWW Document], n.d. URL https://www.forbes.com/sites/brentdykes/2017/06/28/big-data-forget-volume-and-variety-focus-on-velocity/#1b874bb46f7d (accessed 2.7.20).
Equifax Data Breach Settlement [WWW Document], 2019. . Federal Trade Commission. URL https://www.ftc.gov/enforcement/cases-proceedings/refunds/equifax-data-breach-settlement (accessed 2.20.20).
NW, 1615 L. St, Suite 800Washington, Inquiries, D. 20036USA202-419-4300 | M.-857-8562 | F.-419-4372 | M., 2019. Americans and Privacy: Concerned, Confused and Feeling Lack of Control Over Their Personal Information. Pew Research Center: Internet, Science & Tech. URL https://www.pewresearch.org/internet/2019/11/15/americans-and-privacy-concerned-confused-and-feeling-lack-of-control-over-their-personal-information/ (accessed 2.20.20).
Offsey, S., 2017. What is Customer Journey Analytics? Pointillist. URL https://www.pointillist.com/blog/what-is-customer-journey-analytics/ (accessed 2.20.20).
Smith, A., n.d. Making The Best Use Of Customer Data [WWW Document]. Forbes. URL https://www.forbes.com/sites/anthonysmith/2018/12/20/making-the-best-use-of-customer-data/ (accessed 2.20.20).

M

Music video by Rockwell performing Somebody's Watching Me. (C) 2004 Motown Records, a Division of UMG Recordings, Inc.

Comments

  1. Very detailed analysis and informative post! Great work Jack!

    ReplyDelete
  2. Well-written, and interesting blog post! I also think that especially the protection of personal data emerges as a key challenge for markerters. Thanks for sharing, Jack!

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  3. jack is back, very interesting post :)

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  4. Customer data is important for marketing and you have explained how we can implement it efficiently.

    ReplyDelete

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