The Internet of Things is Not About “Things;” It’s About Data
OREANDA-NEWS. May 04, 2016. By now, everyone will have heard predictions that there will be over 25 billion connected devices by 2020. If you read the techno blogs, the Internet of Things (IoT) will be all about new gadgets that we’ll all be connecting to the Internet. A WiFi chip inside, add an app and that’s all you’ll need. But instead of focusing on all these new devices, it makes much more sense to check out what it all delivers. And that’s when it all becomes about data.
Rather than a technological revolution IoT could sooner be described as evolution. The hardware components that make smartphones such a success are so small and cheap we could easily put them into all kinds of other devices. The manufacturers of devices are making such a lot of fuss about it, that if you just take the marketing content into account it seems as if it’s mainly about being connected to the Internet. Nowadays you can buy bed covers, egg trays and even bicycle locks that are connected online.
This all seems so very convenient that it makes you wonder how we managed without it. But, like I said, it’s all about data. In itself, having (lots of) data is not the issue; it’s how you apply it.
First of all though, it’ll be fascinating to analyze what kind of data all this will provide.
(Big) Data-driven marketing
What we can say with some certainty, is that the amount of Big Data that’s been harvested during the past few years pales, into insignificance when compared to the data generation and aggregation that will take place during the next few years. And the role of data is crucial for the sustainability of companies.
This is also evident from benchmark research into data-driven marketing in the Netherlands, carried out by 2bMore. Of the surveyed companies, 22% felt they would expose themselves to significant risks if they fail to get their data-driven marketing in order this year. The research also showed that 54% of companies admit that they’ll lack the necessary connection to their customers if they don’t get their data-driven marketing in order.
How do you assess the growth potential of your company?
With data-driven marketing |
Without data-driven marketing |
|
Excellent |
26.8% |
0.0% |
Good |
61.0% |
19.5% |
Same as last year |
12.2% |
31.7% |
Poor |
0.0% |
43.9% |
Very poor |
0.0% |
4.9% |
Of the surveyed companies, 87.8% foresee good, or excellent, growth potential through using data-driven marketing, while only 19.5% expect to enjoy growth without it. Furthermore, without data-driven marketing, almost half of these companies expect their growth to be poor to very poor.
The role of the IoT
The IoT will further intensify the effective monitoring, analysis and application of data. The possibilities it brings will hugely increase our ability to monitor and measure everything that we do in the world, from the preventative maintenance of machinery to providing more data in our customer-engagement platforms. The challenge will be to design systems and business models that can optimally deploy the information within that data.
If we succeed, the IoT will create an endless feedback loop of user data. At the moment, data relating to the use of products and services (and data used for product innovation) is still largely an unknown quantity. But the IoT has the potential to make it more transparent and manageable.
Products will then become instruments for customer engagement. Physical products with a digital and personalized service layer will be able to assimilate themselves to usage patterns and preferences, thereby increasing their value over time. This will present new opportunities for additional services, based on usage and subscription models. And more value can be added because products will be easier to connect with similar products and services.
Four types of data in the IoT
1. Status data
Is the cooling system of the refrigerated truck working yet? Are all the fans in the server room switched on? This type of status data is the most basic form of performance data. See them as digital feelers in the physical world that make it possible to detect potential failures and inefficiencies.
2. Location data
Has the client’s shipment arrived yet? GPS only works outside. By using different solutions, monitoring is also possible inside, such as one for pallets loaded with products for an e-fulfilment assignment.
3. Automation data
As more and more processes become automated, it also becomes more important to monitor the performance and effectiveness of these processes. This applies equally to the sending of an event-triggered email as the control of a fleet of delivery drones. All this automation generates new data that should lead to the optimization of that automation. As yet, it still has to be done by people, but thanks to self-learning systems, automation is increasingly carrying out self-analysis and self-improvement.
4. Actionable data
Data is extracted from the above-mentioned types of data and then analyzed so that actions can be defined. The benefits from all this data are derived by subjecting it all to algorithms and analysis models.
The why
As we have learned from the Golden Circle management theory, companies that are currently enjoying success have mainly distinguished themselves by building on “the why”. If, as a company, you have a real drive to change something, your chances of success will be greater than if you have simply spotted a gap in the market and fill it.
That said, a crucial element of the why is having some insight into what your customers think. And this is where data can play a crucial role. Tesla, for example, can follow all its vehicles remotely, including the driving style of the drivers, how the vehicles react, and under which circumstances it all takes place. The IoT data plays a key role at Tesla, both in the company and in its interaction with its customers.
Challenge: from user interface to artificial intelligence
In a world of software, apps and screens that come in a variety of shapes and sizes, the user interface was the distinguishing factor. Appealing and smart design remains the norm, but it’s becoming scarcer. There’s a clear shift taking place. Data-driven marketing and marketing automation is fueling the trend, and the smart use of data is the differentiator. But this is a challenge. For many companies and marketing departments, algorithms, APIs, data-management platforms and the effective use of these instruments are much more difficult than just designing screaming pixels in an app or on a website’s landing- or check-out page.
Advanced algorithms, together with a burgeoning mountain of personal and contextual data that’s ripe for exploration and discovery, can only mean one thing. Intelligent software, with data as the raw material, is about to become the new user experience.
Don’t set too much store in KPIs
The bottom line is that data now plays a bigger role and can be applied in many more ways than companies currently realise. These companies often wait too long because they find it too difficult to link it to a KPI. And all too-often in traditional businesses circles, no KPIs means no budget. It’s a missed opportunity. Technology is moving so fast that you have to keep up to know what it can all offer. In the current economic climate waiting for the right insight is no longer advisable. When it comes to the analysis of data and the creation of insights, trial and error is the best and quickest way forward.
About the Author
Ubbo Maagdenberg, Founder and CIO from Emark, Platinum Marketing Cloud Company
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