Marketing Automation Best practices and Data Modelling

Why deploying the Marketing Automation Best practices and understanding of Data Modelling are critical for brands:

Being a Marketing strategist or a customer success manager (CSM) has its own challenge to align with the marketing automation best practices that apply for improvements. We can’t excel in our business goal achievement without applying the marketing automation best practices into the picture.

Here in this blog, The Marketer can learn the concept of implementing Marketing automation best practices and Data Modelling.

Data Visualization:

The whole idea stands on the core logic of understanding of the customer data. When brands are unaware of the content relevancy for an unknown behavior, then it becomes difficult to expect results.

Segmentation is one of the key practices that marketers should follow to bifurcate the audience as per their product affinity or at times channel affinity. Heavier the segment criteria, more refined are the audience. Data Visualization is one of the key metric of data modelling.

Brand need inputs from the website data to know the browsing patterns, purchase analysis to further gauge the customer needs. Thus, Data modelling understanding is the key. The Inflow and out flow of the data is a make or break for any brand.

This helps brands to Improving the data consistency, enhances data quality, supports business intelligence, facilitates data integration, and reduces data redundancy.

This gives brand the high ROI and low churn.

Data Modelling blueprint & workflow strategy:

Every strategy germinates in a marketer’s mind. But that needs to be visualized first with a simple blueprint layout. It could be done on a whiteboard or a paper or a digital slate, but it needs to be done.

This helps marketer to create a straightforward path to achieve the desired business short- and long-term goals. Then marketer starts on creating necessary elements to reach there like channels, data, content, webhooks etc.

We can call this process a dry run.

In this, Brands can define a step-by-step action plan with expected timelines and results. Ultimately, Brand end up creating the same with a journey builder application. Marketing Automation Best practices is effectively applicable only when the brand has the fair idea about Data points, User behavior, preferences, interest, and preferred communication channel.

Aggressive Timelines:

The workflow strategy should be based on a calendar theme. Be it festival based planning, public holidays, or any other occasion, Brand need to have an engagement timeline. When to connect and when to give a break, this needs to be augmented into the strategic mind and overall plan. The Marketing Automation best practices helps brands to engage, converse and repeat the uses.

Time gaps between 2 communications need to be humanly logical. We must give space to our customers. At the same time, this should not be too far as well, as we can’t risk a lead due to delayed engagement.

So, a marketer needs to fix up his total relative time span of a marketing journey as well as intermediate time gaps of communication activities. For example, Brand can use ‘wait for events’ trigger for making this smarter, which is available in most journey flow builders. Ultimately, it can only possible if we have clarity of data modelling and follow the marketing Automation best practices.

Data Segmentation and filtration

Data modelling can help brands to enriching the database as much as possible. This is the best way to ensure refined data. While brand create segments, it becomes much easier to classify data with a greater number of customer attributes and customer behavior activities.

Connecting CDP data can give an eagle’s eye view to identify the right target for a specific product or may be a service. If brand maintain a unified view of a customer across multiple touch points, then it helps brand to understand their preferences. Brands can connect their potential and loyal users at right time via right channel and with right content.

A unified view of the user helps further in curating a more personalized approach to reach them. Thus, one of the objectives of implementing Marketing Automation best practices to get the unified view of the users and brands can reach out to their customers where they are.

Hyper-personalization:

Every communication touch that brands is having with the potential customers should be able to take them to a personalized space, which can relate him to brand content.

Simply meaning, make the content hyper personalized if possible. That can lead up to business goal activity. This will include web connectivity and App connectivity to make brand’s content connected with latest online behavior-based suggestions. Hyper personalization considers as one of the most critical Marketing Automation Best practices implemented by brands at each campaign, channel and customer journey level.

External Data intelligence:

Data intelligence applications are making speedy advancements to change the marketing scenario. Platforms like CDP, CRM, BI and segment management are very well creating predictive analytics to understand the customer acquisitions and churn behavior.

Social feedback engineering is one of the key practices to include generic data across a large database. We can’t ignore our customer pulse, which comes out in true colors on social platforms. Somehow or other, Brand need them in the marketing automation’s scheme of things.

So naturally, the marketer can’t ignore the opportunities coming through them and somewhere must implement the marketing automation best practices.

Improvisation as practice:

Running an automated workflow is not a straightforward line activity. Brand might have to encounter errors, design failures, lower than expected ROI to name a few. This is natural to happen when marketers are trying to implement new strategies, marketing automation best practices and techniques. Which is why, a marketer or a person who designs these setup and flows should embrace improvisation as a humble friend.

This simply means doing trial and error activity till the expected results are visible. Although brand should plan the stepwise program during dry run, there can still be room for improvement during the actual executions. Brand can start with test environments to minimize the production level impact. Implementing the marketing automation best practices during the testing face is the key as brands can be confident about the scale and expected ROI.

Conclusion

A marketer will need to advance with technology along with the marketing sense and experience. It would not be an overnight turnaround, as trials and subsequent errors would be there to make the journey self-evolving.

The best tools and best external application connectivity will ensure that Marketers are in sync with customer expectations and the desired business goals. By following Marketing Automation Best practices, Brands can define clear goals and objectives, develop a customer journey map, segment the audience, use relevant and timely content within the campaigns, Optimization of content and use attention-grabbing CTAs with an objective to get maximize the ROI.

Keep the above Marketing Automation best practices and Data Modelling as a part of the engagement and Implementation plan, Brands will only gain positives from them.

Also Read- Exploring the Features, Advantages, and Benefits of Email Marketing

Written By – Amit Bhateja