Analytics isn’t the final destination. At Syneractiv, growth is. With Growth Miner, we don’t just dig into data — we transform them into action, into results, into growth. In today’s marketing environment, you’re up against fragmented systems, evolving privacy norms, and ever-higher expectations for ROI. It’s no longer enough to describe what happened; you must predict what’s coming and engineer what to do about it. Growth Miner bridges that gap. We start by treating data and insights not as outputs, but as raw material. Those are the “unfinished goods.” Our job: refine them into growth engines. This isn’t about dashboards for dashboards’ sake. It’s about delivering decisions you can act on, campaigns you can deploy, and growth you can measure.
Your brand is your foundation. With Brand Miner, we begin by establishing the mission and the objectives. Through strategic brand discovery, we uncover what’s working, what’s lagging, and where the opportunity lies. We map out the current go-to-market strategy: strengths + challenges. We hold stakeholder interviews (Voice of Customer) and dive into exploratory data analysis (EDA) to surface unspoken assumptions and potential misalignments. We align hypotheses to stakeholder perceptions, so that when modelling begins, everyone’s on the same page. This early diligence matters: when models overturn initial hypotheses, you’ve got buy-in. When you launch campaigns, you’ve got clarity.
ESTABLISH CORE MISSION PARAMETERS
By the time any analytical project has been commissioned, it should have gone through some major vetting of the current or “as-is” state of the project with key stakeholders including interim owners and end-users.
It is critical to have a first-hand understanding of key stakeholder assumptions, perceptions, and expectations and of any gaps in analytical parameters and stakeholder expectations. We accomplish this through a Voice of Customer (VOC) Analysis (a.k.a “stakeholder interviews”) and Exploratory Data Analysis (EDA).
VOC & EDA enable us to conduct a root cause analysis and develop initial hypotheses based on stakeholder beliefs that data modeling will either prove or disprove.
At this point initial hypotheses are shared with key stakeholders along with any initial insights from the exploratory data analysis.
This is important because should the data modeling in fact end up rejecting some of these initial hypotheses, this initial discovery and due diligence will be pivotal for stakeholder buy-in.
Consumer Drivers is a Deep Learning enabled consumer propensity-based segmentation analysis that segments consumers across their journey to ensure minimum attrition of high value growth segments at each stage. This is a hierarchical micro-segmentation approach that recognizes that the same consumer has different priorities at each stage of the journey and marketing communication and content strategy should be optimized accordingly. We accomplish this by enabling customization of creative, content and touchpoints by segment personas and journey stage attributes.
A combination of Machine Learning models is used in Consumer Drivers segmentation methods, including Random Forests, K-Means and Hierarchical Clustering.
These use a combination of your first-part customer data (from your CRM) as well as privacy-compliant 3rd Party segment level audience attribute data. The segmentation output can be directly funneled back to your Customer Data Platform (CDP) or to your campaign activation partner.
Measurement without prediction is hindsight; modelling without business sense is hype. With Demand Miner we unite both. We identify internal and external drivers of marketing outcomes. We predict shifts in market share under competitive scenarios (“what if …?”). Our proprietary algorithm dynamically recalibrates in real-time, maintaining relevance in a shifting landscape. Our model spans first-party user-level logs, third-party audience attributes, digital clean-rooms, walled-garden placement data (CTV, OTT), offline media & promotions—delivering a privacy-compliant, omnichannel, cookieless attribution framework. What this means: you can explain past performance and forecast future outcomes. You can plug outputs back into your activation platforms (e.g., cleanrooms like Google Ads Data Hub) and optimize.
We place equal focus on explanatory and predictive prowess because there’s not much point in explaining history if we are not able to do a reasonable job of anticipating the future.
Demand Miner is a predictive -powerhouse disguised as a campaign measurement solution.
It both identifies internal and external drivers of marketing outcome metrics and predicts market-share outcomes as a result of wargaming competitive scenarios. We leverage a proprietary algorithm that adjusts models in real-time to improve predictive performance.
Syneractiv’s multi-level modeling approach spans audience user-level data from first-party logs or digital cleanrooms, audience creative, network/genre & placement-level data from walled-gardens and Connected TV (CTV) platforms as well as traditional offline media and promotions to deliver a true cookieless single-source and privacy-compliant Omnichannel Attribution Model.
And the model output can be loaded back into cleanrooms like Google Ads Data Hub (ADH) to deliver cookieless remarketing optimization.
