Once upon a time word spread of a marvel from India coming to a town in ancient Persia. A delegation had brought an elephant. Late at night, six curious men entered the dark warehouse where the elephant was being held. They could not see the elephant. So, they groped about with their hands. One touched the elephant’s leg and said it was a pillar. One touched the trunk and said it was a water-pipe. One felt the ear and called it a fan. Another put his hand on its back and said it was a throne. One felt the tusk and thought it was a spear. The other stroked the tail and said it was a rope. Each one saw the elephant differently. But if they had held up a lantern to see the elephant, they would have seen the full picture.
The Problem: Too Many Data Silos
Fast forward a few thousand years: most companies face a similar problem. We all want a well-functioning marketing system. But we know from painful experience that we often end up with complex, fragmented systems and different data sources—online versus offline, reach versus activation goals, below the line, inbound, outbound, etc. The data is there, but each stakeholder only sees their own silo and no one has the big picture.
For Artificial Intelligence to be trained effectively, it should learn the right things, namely what adds value along the whole marketing funnel—not just what the Click-Through Rate shows in one system or the cash flow in another. If we break down data silos, we can integrate fragmented data systems across the organization to create a unified collaborative data environment, enabling more efficient workflows and better data-driven decisions. We can ask better questions about the whole picture of our business operations.
If we have 10% more sales, is that always good? What if the market grew by 20%? Am I actually losing market share even with 10% more clicks? Let’s say I want to run an ad campaign. At what time of the day should I run the Facebook or Instagram ads? How much budget should I put in?
Looking at the Whole Picture
A realistic assessment of what we are dealing with is of course crucial. But insight alone does not make a company more successful. Only those who can incorporate insights into their planning and implement their plan can get ahead of the market and increase their Return-On-Investment.
Most organizations struggle to transform this wealth of data into meaningful business outcomes. They may be drowning in data, but they often lack the ability to extract meaningful insights to help marketing decisions.
A media mix represents the complete range of channels and tactics that we use to connect a product with its target audience, e.g. traditional advertising, grassroots campaigns, digital ads, social media platforms, email marketing and landing pages. For maximum ROI, our media mix should be adjusted continuously in alignment with our targets. We need to use the best sales arguments and advertising materials – these are ultimately the steps that generate revenue. A well-integrated solution must go beyond pure analysis – it must bridge the gap to implementation.
The Solution: Data & AI-Based Planning and Implementation
Together with our partner marcapo, we have shown how such a vision can be realized. marcapo, Europe's leading provider of marketing portals enables local retailers of major brands to create, book and manage local marketing campaigns with a very high degree of automation. marcapo works with NEUTRUM.AI to produce intelligent, realistic, promising planning based on Big Data and analytical AI.
NEUTRUM consolidates data from all advertising channels – from sales catalogs to movie theater advertisements, from retail media to Instagram. For each retailer location, the platform determines local demand indicators, population segmentation, purchasing power, weather, and so on. We use AI to uncover patterns (e.g., seasonal fluctuations), correlations (e.g. does rain increase advertising performance?) and interactions (e.g. radio and Google Ads). Our system provides the marcapo platform with realistic target figures and an intelligent media plan for each retailer: What budget and what media mix should they use, when and where?
That is where marcapo comes in: the local retailer automatically takes in the right advertising content for a given media plan – in all recommended formats, localized and ready for use. If changes need to be made, the retailer can adapt and book the content as well as the media plan with a single click. The campaign is then automatically launched and documented across all channels. The results are continuously fed back into the system, further improving NEUTRUM’s AI models. The accuracy of target figures, recommendations and media planning continues to increase – thanks to training with historical and recent market data.
The combination of planning and implementation – based on the interaction of company and market data – acts as a self-reinforcing flywheel for ever increasing ROI. No need for additional analysis, modeling or reporting.
A Client’s Success Story
KüchenTreff is one of Germany's largest networks of independent retailers specializing in selling, planning, installing and renovating kitchens. If you want to advertise for KüchenTreff, you may want to ask:
What is the demand for kitchen furniture and supplies? What can I sell for kitchens in this area? For instance, I may want to have a forecast of how many kitchen cabinet panels I can sell in October. What can I realistically sell at this location? Can I sell more in Potsdam or in Oldenburg? What would be the best media mix for my advertising?
NEUTRUM brings visibility into the local success factors (e.g. purchasing power, new building permits) and realistic sales expectations. Every local partner will have access to the relevant information. NEUTRUM calculates the best media mix to maximize a retailer’s sales potential: when and how often and on which channels should they do advertising in order to get the best return on every advertising dollar.
The marcapo portal presents the recommendations as an interactive media plan and automatically stores them with brand-compliant advertising content tailored to the partner. The local retailer can review the plan and advertising content, making adjustments if needed, booking them at the touch of a button.
Therefore, the experts can concentrate on selling and building kitchens. The rest runs automatically with AI models that continuously learn from the results of the campaigns and the changing market.
German