Big Data Analytics

When we wite on Big Data Analytics we are thinkig to share a vision to create value for the reader. But Analytcs if it is not inserted in an company with a "culture of data" to the whole organization has a limited impact and it is not enough to create value.

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"Culture of data"

Data often is confused with database or an excel sheet because it is the more simple immagine that we have. But data in our society is much more because data is realated to our behaviour and therefore in a firm is everyware. Data is a touch on an App, is a swith for a free wifi connection, is our position, is a tweet, is a post, is a payement with credit card, is a payment with an app. On the other end in a firm data is the list of the clients and their locations...

Inside an organization data is everyware. Is in Huma Resorser Office with a list of employees...

etc etc

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When we talk about analytics we have to divide looking to the business objectives we want to achive:

• Analytics focusing on gaining insights

• Analytics aiming to develop data models for decision making

Usually insights are the basis for business and marketing instead models are part of more sophisticated research to support the creation of new products or business line in ceneral for more strategic decision.

In any case, the developed insights and models can create value for firms in three ways:

1. Decision support for marketing and business

2. Improved actions and campaigns

3. Information-based products and solutions

The examples could be

• where to allocate their marketing budgets

• model can show the specific effectiveness of an advertising channel or the usage of a particolar service

• Results of a model can show the specific effectiveness of an advertising channel: An important example comes from Lisette De Vries in 2017 showed the limited influence of social media on acquisition, one could question whether a firm should heavily focus on social media to attract new customers. In this case they used a model VAR "vector autoregressive modeling"

Leeflang et al. (2014) distinguish between two different models that can be developed to drive marketing decision making:

• More sophisticated models developed to tackle specific marketing problems

• Standardized models that have become important tools to improve the quality of tactical marketing decisions.

The marketing literature has identified many standardized models (e.g. ScanPro), which aremainly delivered by marketing research agencies such as AC Nielsen, IRI and Research International (Hanssens, Leeflang, & Wittink, 2005). These standardized models can be filled with available data within firms and research agencies. We expect that research agencies will provide more standardized solutions on how big data can be integrated togain customer insights and estimate the relationships between marketing instruments and marketing outcomes.

The improvement of actions and campaigns is mainly relevant in a CRM environment. It mainly has to do with whom to target, when to target and with what message. It has been shown that through:

effective selection of customers,

the ROI of campaigns can be improved (e.g. Bult & Wansbeek, 1995).

customization of messages and offers, specifically in an online environment, can be very valuable (Ansari &Mela, 2003).

In a big data environment this now occurs in real-time, and is also known as

behavioral targeting. This can, however, have negative side effects as it may be consideredintrusive (Van Doorn & Hoekstra, 2013).

A relatively new development in the era of big data is the use of results of analyses and models to develop information-based products and solutions that specifically focus on customers to create value for these customers.

For example, a novel player in the Dutchbanking sector, KNAB bank, is explicitly providing

data-based solutions to their customersto advise them how to use their available money (e.g. put it in a savings account). The Dutch railways provide a service to their customers in which, based on actual informationon traffic and trains, the fastest transport mode is recommended (Leeflang et al., 2014).

Nobel prize winner Rich Thaler believes that these solutions, either developed by suppliers them selves or by other, frequently independent, infomediaries, will become important in helping customers to make more informed decisions (Thaler & Tucker 2013)

Lisette De Vries 2017:

https://www.researchgate.net/publication/317257815_Effects_of_Traditional_Advertising_and_Social_Messages_on_Brand-Building_Metrics_and_Customer_Acquisition