Streamline customer data for better marketing results

Streamlining customer data can not only yield great results but also reveal the returns to your marketing investments. Today, marketers are working on siloed systems which account to data disconnectivity and improper measurement.

In the current state of affairs, marketing activities conducted could be highlighted as traffic/visitor generation, where marketers spend hordes of money advertising on social sites, search sites, and affiliate sites. Traditional marketers use TV ads or print ads to create awareness about their products. As online advertising are measured, you can get a fair view on how these investments performed. But the truth is that these investments only yield when customers who see the ad also make a purchase.

As most of the online advertisement drive traffic to an asset like a website or a mobile app, it becomes a prerogative to engage them all the way to the purchase. Else the entire objective of spending to acquire traffic turns to be a disaster. Marketers have stepped up to offer personalized messaging when the visitor is on the asset. Marketers bank on personalization tools to engage visitors on the website and indirectly store this interaction information in another silo.

Email Marketing is another priority tool that makes it to the marketing quiver. Email tools are today used for bulk campaigns and 1:1 messaging. Though these tools are used to communicate with prospects, lead-lists, the entire information about mail responses is stacked in another silo, breaking the flow of a customer journey.

While the previous case belongs to the mail marketers who manage MQLs, the sales heavy organization use a different tool to manage their SQLs(Sales Qualified Leads). These lead management tools (SalesCRM) are now connected with email tools giving sales folks an integrated communication channel. However, the system might be isolated of web behavior of their prospects

Though there has been some evolution in some of the marketing platforms that offer integrated solutions, they work for a group of identifiable customers which might not necessarily serve the entire crowd coming from your online ad campaigns. They might pick up the hook when the visitor fills the form but cannot run personalization campaigns to entice the visitor to fill the form. So visitors driven from ad campaigns are lost if they don’t fill the form. Moreover, when the visitor comes back, the tool is unaware and treats him like a new visitor.

With such disconnects, it is more likely that the probable purchase conversion could be lost making customer acquisition an expensive affair. Just like customer acquisition marketers, retention marketers also face disconnects within customer data. While some retention marketers just stick to their CRM application, they lose out of customer behavior data collected at touch-points. Some retention marketers opt for loyalty systems to run retention campaigns and this ends up another silo of customer information.

Lots of money is spent on bringing these silos together and creating a unified customer view. Due to lack of appropriate tags to connect customer data between two silos, marketers end up with incomplete customer journeys, leading them to make inaccurate decisions affecting campaign effectiveness.

This unplanned data organization is expensive to any data organization and can prove economically dangerous to make further investments without fixing the foundation.

To save themselves from these redundant investments, organizations need to organize their data and make sure customer data is seamlessly connected across all touch-points, which will help marketers exactly know customer states and intent, which will allow them to strategize their personalization campaigns for higher effectiveness.

To organize this data, we attempted a bottom-up approach by first structuring the business goals and mapping the customer’s journey to it. Every business has an ulterior goal of revenues which convert to profitability and sustenance. As customers are the primary revenue channel for all business, it is only logical to track down the revenue path of the customer.


The path of the customer starts when they have been exposed to the brand through one of the advertising campaigns all the way till they turn valuable or profitable. You can break this path into 5 stages which make it easier to identify and set relevant personalization campaigns.



The logic of classifying customer states are as follows

(a) Awareness/Visitor Generation  – Visitors who land up from Ad campaigns and are identifiable by IP addresses only are termed as an Anonymous visitor. You can engage with them only on the website or mobile browser.

(b) Prospects – Whenever these visitors with IP are resolved with an identifier like an email id or a phone number, we term them as Prospects. Prospects can be contacted directly using the resolved identifier. Email Lists that are imported for Mail campaign management can also be termed as a Prospect as we have an email identifier. This prospect state can be further broken down to MQL/SQL states further drilling down to hot/warm/cold stages.

(c) Customers – Whenever these prospects make their first purchase, they achieve the “customer state”. If the business is a one-time sale, you have achieved the end state of the cycle. Businesses who offer various products or expect repeat sales would have to align their customer data for the rest of the journey

(d) Repeat Customer – Whenever a customer makes a second purchase is moved into this state. This repeat reveals the intent state of the customer exhibiting repeat purchase behavior. However, it is not necessary that the business has profited over this customer even after multiple purchases, as the marketing spends over this customer might have exceeded the total transaction value at a given point.

(e) Valuable Customer – Whenever the total transaction value exceeds the marketing spend of a particular customer and the customer score is well above the RFMS score threshold, the customer is termed Valuable.


Now between the customer states lies the conversion process, where the objective is to entice the customer to move to the next stage. As illustrated in the diagram below, you can see three engagement processes, that exist between these states.



For every visitor identified as Anonymous, the visitor engagement workflow can be triggered to convert them to prospects using insights deduced from past session behavior.

For every visitor identified as Prospect, the prospect engagement workflow can be triggered based on sub-states or stages combined with behavioral insights

For every visitor identified as Customer, the retention engagement workflow can be triggered based on customer segments.

Within these macro processes, you can set micro-workflows between sub-states and segment types. Using Plumb5’s real-time propensity scoring model, you can allow the machine to create microsegments and trigger workflows based on rules.

Based on score range or segment types, configure the rule engine to fire a communication template that dynamically picks content relevant to the user and target effectively.

Between Scores and rules, marketers will be able to run conversion campaigns, recommend or upsell/cross-sell products at unit scale.

With this framework in place, all you need to do is map your customer touch-points to the stages and processes. This will reveal the possible path patterns between touch-points. This allows you to automate each of your processes across any touch-points enabling omnichannel experience for your customers.


Graph for illustration purpose only

With this, any marketer can manage and personalize communication for tens of thousands of customers using machine automation. The marketer’s task would be reduced to scoring data and tagging personalized content.

The other advantage that this data organization brings is to provide the machine with an ability to learn and make decisions, converting it to an AI machine for customer marketing.

To dig deeper into the data organization, click here to view the logical data model, which is designed with a customer as the primary entity.

If you are wondering if this would fit into your business type, the revenue path is applicable to every business. What really changes would be the active customer touch-points, based on business preferences.

Based on current market practices, the chart below shows touch-points actively pursued by businesses to interact with customers.



Apart from pure-play e-commerce companies, most businesses still have a mixed play between online and offline transaction touch-points.



  1. […] A unified architecture in Plumb5 can iron out data obstacles with the help of pre-set tags for both advertising channels and brand engagement channels (email/website/app/social pages). This allows the unified customer data to stack data from all channels and create a journey all the way to the conversion milestone. This allows you to make sure that the incoming traffic are relevantly engaged based on session behavior and move them to an identifiable prospect segment, where further engagement to that user is addressed in lesser expensive channels like email, SMS or apps. Click here to read more on streamling data from the first instance […]


  2. Great charts, and this article helps explain that it’s not just the amount of data, it’s the organization, analysis and mining that helps businesses and marketers separate the signal from the noise.


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