Connecting the dots is an eternal quest of the human condition. We all continue to find meaning by peering into our past and trying to predict the future. To quote from Steve Jobs’s famous Stanford speech

“Again, you can’t connect the dots looking forward; you can only connect them looking backward.”

-Steve Jobs

There’s a lot to learn from looking backwards, but how far along do we peer into history so that our future actions are meaningful? Most importantly, what dots do you choose to connect? How do you unravel these hidden insights? This is a powerful question and motivation that has troubled various disciplines of study, from philosophy to data science.

Marketing is one such discipline that could definitely benefit from such deep retrospection. It is a discipline that is filled with urgency, the need for quick decision making, the need to be creative yet accurate and deliver high impact. Yet, it’s also one of those fields where connecting these dots doesn’t happen that often, the limitations are time, money and resources.


Glance would like to introduce the Intelligent Marketing Graph, a new perspective to craft meaningful marketing journeys. Marketing Graph is a new way of looking at data and creating better future outcomes.

Marketing Graph connects all-important entities, data, metrics across all the marketing channels. It bridges the gap in data understanding through context and relationships. It surfaces the hidden connections to the whys and what-ifs in marketing data.

Marketers are the “Masters of the HOW.” They know how to solve problems and build momentum; it’s the whys and what-ifs that sometimes trip them. The mystery in the marketing world comes from whys and what-ifs. The scenarios often are similar to:

  • What if LinkedIn could drive more leads?  
  • Why did the campaign last week not yield the expected results?
  • Why did the cost per lead increase YOY?
  • What if the allocation was more towards Google Ads than Twitter?
  • What if the email open rate could be increased by 3 percent? Would that lead to a more powerful funnel?

Some of the what-ifs and whys are quickly answered by experience and some simple experiments. However, the world of marketing is fast and changes dynamically. There isn’t enough time in the world for a marketer to model or implement all permutations and combinations available in the marketing context. Also, there isn’t enough time to experiment with all scenarios, so Marketing experts need to take bets daily on previous experience and with limited data at hand. That data is also very single-dimensional. Marketers continue to  struggle with the following problems:

  • Making the right marketing decisions on channel allocation?
  • Figuring out the channels that drive the most ROAS and ROI
  • Hidden impact of the metrics due to their connectedness 
  • Determining effective and right campaign strategies
  • Identifying the right channels and putting the right effort

The world of marketing data is the world of SILOS – yes, DATA SILOS. While initially, we segregate data for ease of access, we slowly start to realize digital marketing is a world of interrelated actions, reactions, and consequences. With our approach of Marketing Graph we hope to solve for the DATA SILOS problem.


Marketing data is just like the interweb. It’s all connected. Various relationships are deep and invisible to the surface, rife with hidden contexts and correlations. An example is an effort on Facebook which impacts response on that channel” but also impacts website traffic and other related social media.

The manifestation of these connections is sometimes unpredictable as the marketer operates from a limited scope of siloed data. Marketers make decisions for a given channel and fail to realize the actual impact, which is usually multi-dimensional and has a ripple effect on other channels. In some cases, marketing actions have a “butterfly effect” with positive and negative outcomes.

This lack of understanding of the impact of actions in a channel or particular marketing activity is what breeds uncertainty, along with its opportunities for information arbitrage. Information arbitrage usually benefits consultants and agencies. These are single-dimensional specialists who focus on improving a specific channel’s performance. It usually means spending quite a bit of money and effort to optimize and drive results from that channel. The truth is that if the marketer had a comprehensive view of all his data, he might end up realizing that an optimized channel for business may still be the wrong channel for his business. 

An example of the above situation is this: Business Acme Inc. is B2B SaaS which drives leads through their website. They spent a lot of time expanding their lead channels to Google Ads and Twitter. After spending a bunch of time and money, they realized that the leads generated from Google Ads and LinkedIn were more effective because they turned into customers with significant value vs. leads from Twitter.


Marketers need to discover the connectedness of the data and interweb of marketing relationships more easily. That need is the origin of the Marketing Graph. 

Technologies like graph analytics come to the forefront. Graph algorithms with AI & ML are becoming the cutting edge of analytics. They increase ML’s context,  add new predictive features to existing models, and increase the predictive power of existing data. They improve trust for explainable AI. Traditional analytics fail to address the problem of growing, changing, and the variety of data seen in digital marketing. Graph analytics with AI and ML allows the exploration of relationships between data objects which reveal newer insights hitherto unknown.

Here is the Gartner Top 10 Trends in Data and Analytics that details the power of graph analytics.

Marketing Graph takes a giant leap beyond today’s solely patterns and trends based AI & ML. It delivers cross-channel data and metric relationships and context with graph analytics to provide insights that marketers never knew existed. These insights go beyond the regular pattern and trend analysis. Marketing Graph delivers actions that improve campaign efficiency multiple times compared to the analysis of an experienced and hard-to-find data-driven marketer for mid-market companies.


The picture below showcases the power of graph analytics to provide usable insight. It recommends a particular channel (LinkedIn) and campaign type (Awareness) to increase open rates on email. This kind of insight is otherwise not discoverable-even by an experienced marketer or today’s marketing analytics tools.

Marketing Graph Insight Showcase

Furthermore, since traditionally, email marketing conversions are high, our recommendation has a massive impact on the overall lift in ROI.


Glance with this announcement will be rolling out the Marketing Graph in the coming weeks, we will begin with Sparks – a data stories based insight in Google Analytics. We will soon follow it up by rolling out similar insights for Mailchimp. 

We need your support through active feedback as you try these features. We hope to paint a better and bigger picture of your overall marketing through the Marketing Graph. We intend to make marketing effective and meaningful.

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