Benefits and Challenges of using Customer Data for marketing

Benefits and Challenges of using Customer Data for Marketing

Managing customer data at the time of high digital competition (e.g. more than 2.5 quintillion bytes of data are created each day (FitzGerald, R., 2019)) is the number one task for companies dealing with large sets of customers data. Therefore, considering customer’s data types will help create a complex approach regarding gaining value from such data as well as possible solutions it should be delivered in (Roberts, J., 2013).

How are types of customer data can help marketers?

Source: Smart insights, 2013 

There are 4 types of data (FitzGerald, R. 2019; Roberts, J., 2013):

Identity data is important to create a buyer persona and personalized communication channels.

Quantitative data is inevitable to use in order to predict buying habits and intentions.

Descriptive data is necessary to analyse to create customer loyalty.

Qualitative data is important to find the best channel to interact with particular customers as well as create customer loyalty.

What are the takeaways of using predictive analytics?

Source: Omni-sci, 2019

Having all this data in real time is necessary for companies to identify the right audience and predict customer behaviour with new trends. The essential part for predictive analytics to work is to organise customer data with Customer Data Platform (CDP). CDP is a software which generates up-to-date customer information from different channels. Companies will get considerable benefits while analysing customer reviews, behaviour patterns, sending personalized messages in right time and in right way.

The main challenges which is predictive analytics will help with (Heger R., 2019):

Source: Econsultancy, 2018

Inconfidence in brand and product. For example, Amazon’s unique system is based on predictions from customer previous purchases to gain quick delivery (new program of one day shipping (GeekWire, 2019)).

Inaccurate matching between supply and demand. Ryanair, when analyses customer data about preferences in travelling, is able to successfully predict demand at a particular time (DeLuca, J. V., 2019).

Using Customer Data Platforms will maintain long-term company-customer relationships and decrease key challenges.

 

References:

1. DeLuca, J. V. (2019) ‘Growing Airlines with Direct Distribution and Demand Forecasting’. Medium. Available at: https://medium.com/yieldr/growing-airlines-with-direct-distribution-and-demand-forecasting-934a1e8c4c9d [Accessed: 16 February 2020].
2. FitzGerald, R. (2019) ‘4 Types of Customer Data to Enhance Your Marketing Campaigns’ Connext Digital. Available at: https://connextdigital.com/types-customer-data-enhance-marketing-campaigns-infographic/ [Accessed: 16 February 2020].
3. GeekWire (2019) ‘Amazon will spend nearly $1.5B in Q4 for one-day delivery initiative as shipping costs skyrocket’. Available at: https://www.geekwire.com/2019/amazon-will-spend-nearly-1-5b-q4-one-day-delivery-initiative-shipping-costs-skyrocket/ [Accessed: 16 February 2020].
4. Heger R. (2019) Marketers: Unlock The Future of B2C Marketing with a Customer Data Platform and Real-Time Predictions. Exponea. Available at: https://exponea.com/blog/predictive-customer-analytics/ [Accessed: 16 February 2020].
5. Roberts, J. (2013) The four key types of customer data for marketing or... how valuable is knowing my customers pet’s name? Smart Insights. Available at: https://www.smartinsights.com/customer-relationship-management/customer-privacy/types-customer-data/ [Accessed: 16 February 2020].