Costs versus added value
Posted: Mon Dec 23, 2024 5:45 am
With all these different tools in use, the customer experience will never be seamless.
“Make experience your business”
Of course it is wonderful, total integration of data. As an analyst, you dream of that. But I wonder out loud how many companies are ready for that, especially considering the costs involved. Axel answers that costs should not be a motive, at least not if the added value is greater than those costs. A truism, of course. Although in practice I often see far too little of that added value directly. Perhaps because changing an organization does not happen entirely automatically? And tools alone are not enough to initiate those changes?
It is precisely because of the fragmentation of responsibilities within companies that different tools are purchased for each part of the customer chain, says Axel. No platform-based integration, but the laborious tying together of different tools. That also costs a lot of money. I see his point, but I still wonder how many companies will see it hong kong mobile phone number that way in the near future. Time will tell, I think.
Use of artificial intelligence
Integrated use of all tools, that is where Adobe focuses in the continuous development of their marketing tools. And artificial intelligence is going to play an increasingly important role in this. “Artificial intelligence gives access to everything that is already available in an integrated way, so that people can do something valuable with it,” says Axel about this.
Big data and data science
Then I am curious how Axel views concepts like big data and data science and where they touch the 'old' digital analytics . According to him, digital analytics mainly provides insight into customer data and customer behavior. Big data goes much further than data that is directly related to customer relationships.
In his view, analytics is especially valuable at operational and tactical levels. Depending on your digital maturity, you move as a company towards data science, where predicting customer behavior is the main focus. That is where you can provide customers with highly personalized experiences and where artificial intelligence makes an important contribution.
“Make experience your business”
Of course it is wonderful, total integration of data. As an analyst, you dream of that. But I wonder out loud how many companies are ready for that, especially considering the costs involved. Axel answers that costs should not be a motive, at least not if the added value is greater than those costs. A truism, of course. Although in practice I often see far too little of that added value directly. Perhaps because changing an organization does not happen entirely automatically? And tools alone are not enough to initiate those changes?
It is precisely because of the fragmentation of responsibilities within companies that different tools are purchased for each part of the customer chain, says Axel. No platform-based integration, but the laborious tying together of different tools. That also costs a lot of money. I see his point, but I still wonder how many companies will see it hong kong mobile phone number that way in the near future. Time will tell, I think.
Use of artificial intelligence
Integrated use of all tools, that is where Adobe focuses in the continuous development of their marketing tools. And artificial intelligence is going to play an increasingly important role in this. “Artificial intelligence gives access to everything that is already available in an integrated way, so that people can do something valuable with it,” says Axel about this.
Big data and data science
Then I am curious how Axel views concepts like big data and data science and where they touch the 'old' digital analytics . According to him, digital analytics mainly provides insight into customer data and customer behavior. Big data goes much further than data that is directly related to customer relationships.
In his view, analytics is especially valuable at operational and tactical levels. Depending on your digital maturity, you move as a company towards data science, where predicting customer behavior is the main focus. That is where you can provide customers with highly personalized experiences and where artificial intelligence makes an important contribution.