The Internet of Things from a Digital Analyst’s Perspective

By Mark Bell posted 11 days ago

  

Introduction

The internet of things (IoT), where devices talk to each other through a network, looks set to expand rapidly in many areas from hospitals to scientific research, into smart cities and into people’s homes. One outcome of this technology, and probably the one that is most attractive to investors, is that it will produce another mine of data for analysis; to better understand the world and our place in it, and how we can improve relationships between ourselves and how we are impacting the planet. This blog post will focus on what benefits the IoT could potentially have for digital analysts and identifying any potential pitfalls and challenges. I will conclude by summarizing the points made and in asking for any inputs anyone might have.

What insights can a digital analyst obtain from the internet of things?

Will it indicate buying habits for FMCG items such as meat, dishwasher tablets, bread?

What about the impacts of trends in diets, fashion etc.? 

One advantage that data from the IoT could bring is the closed loop of knowing when people are running out of items out monitored and communicated by their cupboards, fridges and freezers, coupled with their long term and short term buying habits. This data would enable stores to have the right items in stock at the right time. An improvement on stores solely relying on what is bought against what remains on the shelves: There is still a large margin for error using this stock taking method (store theft, lost items, dishonest staff, etc.) I was once at a presentation given by a director for a large mid-range supermarket where he remarked that their annual unaccounted loss was the same as the profit of a smaller competitor for the same year). Also food is less likely to go past its sell-by-date in the supermarket or clothes to go out of fashion, or season, as stores need only stock exactly what is required, which could have an impact on stock clearance sales. (would there be a requirement for such sales from a retailer’s perspective if there is a minimal amount of stock to clear at the end of the season?)

Fashion stores could know in advance the sizes of clothing they need to stock through IoT data. It may also be helpful for stores and producers to know where their clients store their food, cleaning items, toiletries as this could impact shop layout, packaging design and labelling. Data from the IoT could provide information on when people are renewing their items or making initial purchases. Is it when they run out, when items go off (or are worn out), or when they have found a new recipe?

Potential Issues

The major pitfalls and issues I can foresee are:

What will people’s perception be over yet more data on themselves being produced and stored?

Could the use and availability of this data be seen as being too invasive?

Will the benefits of using items with IoT installed outweigh any perceived or real concerns as to the use of the data? 

What control will individuals want access to regarding the sharing of any data produced by, for example, their fridge or their cupboards? 

What can be done to ensure data privacy, for example ensuring only anonymous data can be used?

What tools will be used to analyze such data? The same tools currently used for web analytics, i.e. Google Analytics et al or something more complex? IoT data, as with any other data, could prove to be overwhelming to the point of useless if not managed and analyzed appropriately.

Finally what impact could any future data privacy laws have on IoT data that are not covered already by existing laws? 

Summary

Insights from data provided by the IoT could have a major impact on marketing, sales, website design and layout as the potential is enormous; knowing what the consumer wants, when they want it, how often they buy it, etc., in far more detail and with more reliability than previously.  However there are downfalls such as; users’ potential issues with data protection, the complexities of ensuring data privacy over such a wide network, finding and using the correct tools for analysis and navigating complex laws around data privacy and the IoT.

I will be interested to read any comments.

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8 days ago

Great post Mark. IoT data is already being used by companies like Apple, Fitbit, Tesla and others but under a different name.

IoT data is commonly referred to as "event level data" or "clickstream data", platforms such Snowplow Analytics and Apache Kafka are the future of digital analytics and the present of some analytically mature companies. You won't see many digital analysts working with this event level data though, this is a role usually attributed to Data Scientists and Business Analysts.

You analyze event level data with SQL, Tableau, Python/R, which are skills that most digital analysts lack, due to the current product-centric skillset approach.

Regarding the data privacy, I think it is up to governments to regulate it. Notice none of the main web analytics platforms (Adobe/GA) are GDPR compliant yet. I'm curious to see how Adobe/GA is going to allow people the "right to be forgotten" or to take their data with them.

For the majority of the people, I don't think they realize what data they are giving or its value. Data can be used for good or bad, without proper regulation we are at the mercy of our imagination, etics, and profits. I do expect government agencies (FTC, FCC, etc) to regulate more over time.

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