Effective Data Management Is the Key to Marketing Automation Success

“Global marketing automation spending will reach $25 billion by 2023, implying a 14% annual growth rate,” a Forrester report.

The investment in marketing automation technology is increasing at an astounding rate. With the availability of modern technologies, it has become easier for marketers to automate their marketing processes for efficient management and to achieve in-time targets. Marketing automation has brought about a paradigm shift in the marketing methodologies with most marketers relying on it for implementing their marketing strategies.

So, is it really necessary to follow the automation trend?

What significance does marketing automation derive in this modern tech-savvy world?

Marketing automation is mechanizing and automating marketing processes through the use of automation tools / software to reduce or even eliminate repetitive and time-consuming tasks like:

Companies that use marketing automation see more web traffic, more buyers, and spur greater retention and loyalty.

Let’s first look at some key statistics related to marketing automation.

• 91% of marketing automation users say that it’s ‘very important’ to their overall online marketing efforts.
• 74% of marketers say that ‘saving time’ is the biggest benefit they see from automation.

Data below shows marketers are going to spend more on automation technology that helps them do through-channel work, real-time communications, resource management, pre-purchase nurturing, and more.

Making Marketing Automation Work

Implementing marketing automation successfully requires a sound strategy that is well aligned with the trend. In addition, the adoption of new generation of digital technologies can ensure an effective management of a large amount of data, real-time execution of automated processes and advanced analytics.

When it comes to data automation in marketing, efficient data management becomes top priority.

Why Is the Success of Marketing Automation All about Data?

According to a report, poor data management and quality is the biggest hurdle which is hindering marketers from generating significant ROIs into marketing automation platforms.

For example, the report found that the major problem for 49% of respondents using marketing automation platforms was of data hygiene issues, such as data scrubbing and de-duplication.

In addition, 51% reported missing data contributed to data quality, while 55% were of the view that incorrect data was a key contributor to poor quality data. More than half of the respondents also reported data decay as a critical challenge, and 26% said wrong formats were causing issues.

As marketing runs on data, organizations have started to count on data quality and management as their top priority. According to the report, marketers are spending most of their time on analytics and reporting, followed by data management, campaign execution, sales support, strategy, and planning.

How to Effectively Manage Your Data

Marketing automation is solely dependent upon the accuracy, completeness, and validity of the data on which the automation tools will run. Outdated and inaccurate data, inconsistency in information and poorly integrated data may not align you with the core objectives of marketing automation, retarding the ability to create relevant, timely and engaging communications, and eventually impeding efforts to increase sales or business.

In the worst case, marketing processes driven by poor data quality can actually hamper customer relationships, as illustrated by various studies.

Data is a business asset, generated by business operations. Effective data management can bring about all possible business outcomes that the marketers are seeking for.

Data Quality

A well-aligned marketing automation strategy will be futile and all your efforts will be in vain if the quality and context of your data is poor. A quality data can definitely make marketing automation successful and help users manage their lead process and build better qualified marketing leads.

Behavioral data — social and web interactions of the customers or prospect, their likes, and dislikes.

Historical data — purchase history, support issues, and known requests.

360 view of customer — buyer interactions across all your channels — web, store, direct sales, etc.

However, marketers must ensure that they standardize the data from across the organization before attempting any database integration to support their marketing automation activities.

1. Assessing the quality of existing data and its degree of reliability and consistency

Data profiling enables the marketers to fully understand the issues with their existing data and determine what steps they need to follow to correct it. Certain data quality assurance tools automate this process, enabling marketers to incorporate their own rules, so the data is not only validated for quality, but also for relevance to the marketer’s specific marketing needs.

2. Converting these rules into processes that transform and correct the data into a common format

A corrected and standardized customer record ensures it will match associated data coming through other channels and legacy systems of data collection. This will ensure that associated customer, product, and historical data is linked to the correct person and that any external data can be appended as per the requirements.

3. The above processes can then be embedded into marketing systems to automate the validation and correction of data at the point of data extraction and to continually audit the data for quality checks to meet defined requirements.

Following these steps will ensure that marketing systems, supporting teams, processes and users have a high level of data consistency, quality, and reliability serving their specific business requirements.

Integration

Stage I

Apart from data quality, integrating the data must be the next step marketers should look into. Marketers need to identify all the sources of information that matters when it comes to the integration process. Once these information sources are identified the second step is to integrate and bring all of them together.

This is the standardization stage for your data. For example, the click-through and web log data is normally kept in Stage II

Big Data sources like Hadoop. In addition, social media channels provide Application Programming Interfaces (API) for retrieving information. Here the actual challenge is about standardizing and syncing all different formats of data into one. Alternately, through the business intelligence platform, you can transform your disparate data formats into logical groupings and subject areas.

The last step in this Stage III

data integration process is ‘rinse and repeat’. The customer’s preferences and tastes keep changing with the time along with the company’s products and services. So, it is important to iterate and refine your data standardization and analytics to achieve your targets.

Conclusion

Marketing technology is fantastic at handling large amounts of data faster and more accurately than we can. If you aren’t using marketing automation you are potentially missing out on opportunities. Dynamic analytic tools and big data can help in building a relationship with prospects based on their business needs and the circumstances in which they operate. You just have to stay focused and tuned in with the strategies that you are working on. With the help of deep buyer insights and use of automated technology, you will be a successful marketer.

Originally published at https://deck7.com.