Skip to main content
Business LibreTexts

3.5: Approaching data

  • Page ID
  • \( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \) \( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)\(\newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\) \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\) \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\) \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\) \( \newcommand{\Span}{\mathrm{span}}\) \(\newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\) \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\) \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\) \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\) \( \newcommand{\Span}{\mathrm{span}}\)\(\newcommand{\AA}{\unicode[.8,0]{x212B}}\)

    Enabling dynamic data

    Consumers today expect increasingly personalised communication from brands. Personalisation is all about relevance. You can only successfully communicate with and add value to a customer if you understand who they really are. The only way you can do this is through dynamic data.

    Many businesses make the mistake of not collecting and storing their data in a single place that can be accessed by everyone. For example, the sales department might have a list of qualified leads, the marketing department might have customer reactions to marketing material, and the CRM department might have access to customer complaints. Multiple data sets within a business pose a risk to customer communication, especially where they lead to irrelevant or outdated information being shared with customers.

    Businesses should aim for a single view of customer (SVOC). This is when businesses have one view of customer data, which is all collected in one place and can be accessed by different departments. However, SVOC on its own is insufficient in today’s data-rich environment. A SVOC is important as a starting point for storing clean data, but because it is collected at a single point in time, it doesn’t account for customer change.


    Read more about the importance of database hygiene (keeping data fresh) in the Customer relationship management and Direct marketing: Email and mobile chapters.

    Because customers are evolving in the way that they use technology and how they consume products, businesses need to evolve their approach to data to keep up. What is relevant to a customer today might be completely different to what was relevant yesterday. For example, customers listed on the database as married may now be divorced, and customers listed with certain political or product preferences may well change these preferences over time. Businesses need to move away from master data focused on a SVOC and toward dynamic data that keeps this evolution in mind.

    Figure \(\PageIndex{1}\): Customer experience and data work hand in hand Adapted From Unknown, n.d.

    As an example, consider a student living away from home, who is provided with a credit card by her father. A SVOC would result in sending marketing material to the father who signed up for the card, when a more dynamic view would take into account who is actually doing the shopping and send the material to her instead.

    Data and customer strategy

    A data-driven view of the customer allows a business to move from organisationcentric to customer-centric thinking.

    Figure \(\PageIndex{2}\): The difference between thinking like a shareholder and thinking like a consumer

    A customer-centric brand will use these five principles in their customer strategy:

    1. You are not the customer. No members of staff should presume to know what customers will like or want. No one person’s hunches or intuition will be as accurate as a large data set. Use research and data to understand what your customers will like and how they will act accordingly.
    2. Your brand does not know the customers as well as they know themselves. The brand should understand their customers, realise that the customers are changing, and be willing and able to use data to track and respond to that change.
    3. Customers are all different: broad segmentation is the same as generalisation. With the amount of data available, brands are capable of very granular segmentation so instead of talking about “All women between 18 and 30 who use makeup”, they can narrow it down to “Women between 18 and 30 who use makeup, are interested in X and Y, who like to consume Z, and who are friends with A and B.”
    4. Customers are constantly changing. Dynamic data is essential to ensuring your view of your customer is accurate and relevant.
    5. Data drives the customer-centric view. You cannot give your customers what they want unless you know what that is and who they are.

    When thinking about different customers using the same type of product, consider makeup brands like MAC and Rimmel. Both brands would target women aged 18–30 years old who wear makeup. However, these brands differ in what their respective customers want from their makeup, what they are willing to pay, what skincare benefits they expect, where they socialise, and what jobs they may have. The more detail you have about your customers, the more you are able to set your brand apart and create marketing messages that speak to individuals.

    In a customer-first strategy, dynamic data means creating that never-ending feedback loop we’ve looked at, of experience out and data in. Everything you do should push out an experience for the customer, and your customer expects that experience to be relevant, personalised, and built for them but in a way that’s not too obvious. Larger, established companies may find it difficult to carry out this major shift in thinking to a customer-first approach, which puts new businesses at an advantage.

    Data and trust

    Consumers are increasingly concerned about privacy. To comfortably share with you the data you need, consumers must believe you will treat that data responsibly and respectfully. Any brand collecting data about its consumers, which should be every brand, needs to work on establishing and maintaining this trust. Trust has three components:

    1. Security: You need to make sure that you can protect customer data from being hacked or stolen.
    2. Privacy: You need to ensure that your brand is compliant with legal requirements regarding what data it is and is not allowed to be collected and what it is allowed to do with that data. You should have a privacy policy outline that is easily accessible to the consumer.
    3. Transparency: Give consumers insight into how their data is being used. Demonstrate how providing access to their data is contributing towards improving their experience.

    Once you establish trust with a consumer, that trust can become a bond that leads to a relationship. The more trust you have, the better the relationship will be. However, if you break the trust by overstepping your bounds in personalisation, spamming the customer, or not keeping their data safe, they will go elsewhere

    Different countries will have different legislation around what brands need to do to protect consumer information, such as the European Union Data Protection Directives of 1995, South Africa’s POPI (Protection of Personal Information Act) of 2013, or Canada’s Personal Information Protection and Electronic Documents Act (PIPEDA). Make sure you are compliant with the laws of the country in which you operate.

    This page titled 3.5: Approaching data is shared under a CC BY-NC-SA 3.0 license and was authored, remixed, and/or curated by Rob Stokes via source content that was edited to the style and standards of the LibreTexts platform; a detailed edit history is available upon request.