Data is to businesses what oxygen is to humans.Regardless of the sector, geography, or reason for existence, data and technology are critical components of any organization.
Marketing technology (Martech) is an excellent example of a business model that heavily depends on data for optimal performance.
Technically, how relevant a Martech firm can stay in the market is determined by the amount of data it has access to, and, without a doubt, this is the scenario in which the majority of Martech firms find themselves.
Data-driven marketing, according to industry experts, may help a firm increase its sales and return on investment (ROI), but this is primarily dependent on the quantity of information about potential consumers or leads that marketers have access to.
Role of Data in the Future of Marketing
Access to customer data helps not only Martech firms, but also brands to better understand their customers. This allows them to correctly predict customer behavior and deliver personalized solutions, or products that satisfy their core needs in the long run.
Ojamu – a Singapore-based MarTech company – was funded in 2019 with the goal of revolutionizing the marketing industry by bringing AI-driven marketing technology to the blockchain.
In an exclusive interview with DailyCoin, Hal Bame, CEO and Co-founder at Ojamu, discusses the integral role data will play in the future of marketing technology.
By leveraging the power of blockchain, artificial intelligence (AI), and NFTs, which make up the entirety of its neural predictive engine, the startup is able to predict the most effective digital marketing strategies for cutting-edge brands.
At the center of all of this, is data, which plays a very integral role in the overall success of Ojamu’s customer offerings.
Bridging the Gap
Given that it is an AI machine learning platform, Bame claims that the effectiveness of Ojamu’s AI solution is largely dependent on the quantity of data it is fed.
“First of all, AI and blockchain technology is only going to work together as smartly as the data you feed it. The more data you feed an AI machine learning platform, the better its performance, What’s really important for brands right now is that there’s tons of data out there. I mean just immeasurable amounts of data online, from habits to trends, to engagement on social media, to podcast uptake, and many others,”,
According to him, the fundamental purpose of Ojamu is to bridge the gap between brands, and the volumes of data that they would otherwise struggle to access. In order to make sense of it all, the startup will employ AI, machine learning, and other smart intelligent toolsets.
The Question of Traditional Agencies
The first step to a successful digital marketing campaign is to collect existing data, and it is exactly this protocol that is used by Ojamu. For the barely three-year-old startup, the journey, from inception, to arriving at their goal, begins with data collection, especially from the brand itself.
“The first step is to get all the data we can, from the brand that we’re speaking with. If you’ve never done anything on social media - fine. However, you can provide us with a response to such questions like ‘what do you wanna do,’ ‘who do you think your competitors are gonna be,’ and other sorts of basic questions,”
Once these questions are answered, Bame explained, the next step would be to sort the responses into categories and analyze them per other competitors within the industry.
Basically, this solution eliminates the role of a traditional agency that, for their part, recommends marketing campaigns to brands largely based on the activity of other brands they have worked with in the same sector.
Using AI-learning for Potential Campaigns
The downside to what a traditional agency does, according to Bame, is that they are limited by the amount of information they have access to.
“For example, a new socks company entering the market might contact four agencies that have previously worked with the largest sock firms. They often argue, on the other side, that this is what we think you should do because we know more than you, we've been in the business for a long time, and we work for all of these major companies. However, no matter what analysis they used, it's all subjective in the end,”
By employing its AI learning machine and neural predictive engine, Ojamu, according to its CEO, basically eliminates the tedious process undertaken by traditional agencies. Moreover, it also recommends digital campaigns to brands based on as much data as it is being fed, and ,of course, thorough market analysis. So what exactly does the process look like?
“Take, for example, image recognition. In terms of banner ads, our image recognition program may suggest that the static picture should show: a person's legs with socks on a bed at sunrise; the light shining through down to the pixel, and so on,”
Ojamu’s language processing program, on the other hand, might propose context, content, hashtags, and other related items. Finally, the AI would advise on how to carry out the campaign, including channels, target markets, and other relevant factors.
“The data says this, love it or hate it, dislike it or like it, this is it and the data is read and then from that data, our AI is recommending the digital campaign that is technically proven to give you the best chance of success,”
Bame described in detail.
Ultimately, Bame emphasized that using data for marketing, contrary to general opinion, “isn’t the future,” but rather, “it’s happening now.” He added that, while AI opens up new possibilities in the marketing world, it relies heavily on data, which in itself is a brand’s most valuable asset.
On The Flipside
- The AI-driven machine learning and blockchain technology used by Ojamu needs to be fed large quantities of data, which could prove to be a challenge, especially for a new brand.
- Because Ojamu’s solution is based on AI machine learning, it may take a long time to collect data.
Why You Should Care?
The breadth of marketing is expanding beyond human capabilities, and it is vital that brands and traditional agencies look to new solutions, ones that incorporate AI-machine learning.
Watch the full interview here: