How To Use Analytics For Cross-Channel Insights

74% of our product signups were tagged as 'Direct Source' in HubSpot—until we asked our users where they actually came from. We included a self-reported “Where did you hear about us?” question in our product's Typeform survey, and the results were telling: → 30.5%: Heard from a friend/co-worker—making word of mouth our most influential channel. →13.6%: Saw a Google Ad first, but didn’t click. This highlights a significant view-through impact that HubSpot tracking misses due to reasons like adblockers or cookie settings. → 9.7%: Selected LinkedIn Ads, and 8.6% pointed to LinkedIn posts, showing that LinkedIn is an underappreciated driver in our signups. → 4.3%: Referred to reading a blog before signing up. The takeaway? To make smarter marketing investment decisions, you need to look beyond platform-reported data. 📍 Combining direct tracking with self-reported insights helps bridge the gap in understanding which channels are truly driving growth. What does this mean for us? 1. Google Ads: We need to model view-through conversions when assessing ROI—clicks alone don’t tell the full story. 2. LinkedIn: Our active presence (both paid and organic) significantly contributes to signups, even if it doesn’t show up in traditional tracking tools. 3. Word of mouth: This remains our strongest channel, emphasizing that investing in product onboarding and customer success is not just retention but a strategic growth lever. Question for you: What channels might you be undervaluing in your current strategy? #marketinginsights #customerjourney #growthstrategy #attributionmodeling #factorsai

I've been talking to a few of marketing teams who have MTA (multi-touch attribution), but are not sure how to look at the data, and more importantly not sure how to do the story-telling around MTA. Here are 3 approaches that I recommend when I talk to them: 1) Deal Story Start by showing the data for ONE Deal or ONE Account. Have it organized on a timeline. A timeline view of a deal reveals a lot about the length of sales cycle, the # of touches, type of interactions, across how many people, types of interactions, etc, etc. And it's very intuitive to understand - and executives love them 🤑 What you're also doing is showing your data. You're saying - this is the data that we're going to now look at the aggregate. Create 2-3 Deal Stories as examples to share with the team. Do this quarterly. 2) Campaign ROI For a given campaign, can you show me the business impact, in terms of # of Opps, the $$ Amounts? This is also a very intuitive way to start with MTA data. Marketers likely already have a Campaign report that shows things like # of Attendees or # of MQLs, or something - and you're simply going to add additional columns with # of Influenced Opps and $'s. You can then aggregate the list of Campaigns by Channel and so on. Create Campaign ROI slides that show the campaign, it's creative/content, audience, it's execution data (sents, opens, attendeds), and business impact. 3) Revenue Lookback. This works just as well with Pipeline, but basically now you're looking at the data from outcomes point of view. Get the total Revenue number for a quarter or year, and then show which Campaigns or Channels were most influential. This type of dashboard is not as intuitive as the first two, so I don't like to start with it, but it's arguably why you bought MTA in the first place. --- Yes, each of these deserves it's own dashboards (or even set of dashboards). What type of stories are you all creating with this data??

I am yet to meet a marketer who fully trusts the data from Facebook or Google reports. And for good reason—they’re biased and don’t account for sales that would have happened anyway. If you're looking to fix this, you need a unified measurement approach. Here’s how: 1/ Unify Your Data Bring data from all channels into one platform. This gives you a side-by-side view: platform-reported insights vs. incrementality-driven insights. Moreover, this helps validate what’s real and uncover hidden discrepancies. 2/ Use MMM for Objectivity Marketing Mix Modeling evaluates every tactic across channels. It even accounts for external factors and uncovers insights platforms miss. For example, we helped a retail brand discover their Facebook ads were driving significant offline sales—something the platform reports completely ignored. 3/ Test Continuously Run geo-experiments to identify tactics driving true incremental revenue. Regular testing helps you remove platform bias and provides evidence-backed insights. 4/ Calibrate Real-Time Reports Use causal attribution to adjust real-time platform data and make precise campaign optimizations. ---------------------------------- Bottom line? Using these methods, you’ll move beyond biased platform metrics. Instead you can rely on true incrementality insights that spurs business growth. Are you trusting your platform reports? If yes, how sure that they're correct. Let’s discuss below.

In today's complex marketing landscape, understanding the true impact of marketing efforts is more challenging than ever. We need to cut through the noise and accurately assess what's driving business impact (e.g., revenue growth). Econometrics offers a powerful solution. By applying statistical modeling to marketing data, marketers can estimate the effects of their activities while controlling for external factors like seasonality, pricing changes, and competitive pressures. This allows marketers to go beyond surface-level metrics and uncover deeper insights into how marketing drives business outcomes. Here's how econometric methodologies can be used to measure and optimize marketing performance: Estimating Incrementality: Techniques like regression analysis and causal inference can be used to approximate the true impact of marketing campaigns, isolating their effects from other influencing factors. This helps identify which initiatives are truly driving incremental revenue. Optimizing Marketing Mix: Through techniques like time series analysis and attribution modeling, the interplay of various marketing channels (e.g., digital, TV, social) can be analyzed to understand their individual and combined contribution to sales. This data-driven approach enables smarter budget allocation and maximizes overall ROI. Identifying Synergies: Econometric models can reveal how marketing interacts with other business drivers, such as pricing and promotions. By understanding these synergies, marketers can develop more holistic and effective strategies. Understanding Customer Segments: By analyzing customer response to marketing activities, audiences can be segmented based on their value and behavior. This allows for more targeted and effective campaigns, optimized for customer lifetime value (CLV) and acquisition costs. Econometrics empowers marketers to move beyond gut feelings and make informed decisions based on robust data analysis. This leads to more efficient spending, improved ROI, and a deeper understanding of customer behavior. How are you leveraging the power of econometrics in your marketing strategy? #marketinganalytics #econometrics #datascience #ROI