How to Use Data Analytics for Marketing Optimization

Thanks to digital transformation, global markets have become more competitive than ever. The democratization of force-multiplying digital technologies has already made it possible for humble small and medium-sized enterprises (SMEs) to face off against major conglomerates and succeed in hypercompetitive markets. Similarly, some larger businesses have also leveraged the same systems to reach previously unimaginable levels of growth.

These remarkable successes, in large part, have only been possible through the smart use of data analytics principles. Through the gathering and interpretation of data, businesses can gain deep insights into trends affecting various areas of operation, mitigating risk and saving tremendous amounts of resources.

Data analytics has proven especially useful in optimizing marketing campaigns and giving businesses a means to glean insights from customer behavior and preferences, often in real-time. However, to be effective at leveraging data, companies must look beyond simple technology spending and prioritize developing a holistic system that puts data first.

If you want help updating your company’s data management systems, get in touch with a data analytics firm Philippines businesses depend on. Regardless of whether or not you want to hire the services of a professional data analyst agency, below are a few best practices that you can follow for creating a data-first environment that simplifies and empowers marketing in any organization.

1. Identify Areas for Improvement. While having a data analytics framework can be advantageous, putting one in place without an immediate purpose can lead to avoidable teething issues and missed opportunities. Before a business invests in data analytics, it must prepare a shortlist of areas to be improved. For instance, a business can prioritize areas like customer segmentation, campaign performance tracking, or the identification of new market opportunities as initial goals after implementation. Doing this can help avoid unnecessary technology purchases and create a firmer foundation that can support more data-centric activities later on.

2. Set Clear, Measurable Objectives. Once areas for improvement have been identified, the business must set specific, measurable goals that keep efforts coherent and maximize available bandwidth. Importantly, doing this creates a benchmark for success, helping avoid scope creep and conserving the momentum of the marketing optimization project. Doing this in the beginning of any marketing campaign can help to keep goals down to simple objectives that could be measured by simple Key Performance Indicators (KPIs) such as total website traffic, conversion rates, or customer engagement numbers. Additions and refinement of objectives should be explored later as the business encounters roadblocks and successes in its data analytics activities.

3. Use the Right Tools for the Job. Various analytics suites like Google Analytics, HubSpot, or Semrush can be used to track and analyze marketing data. Though these tools perform broadly similar functions, some marketing analytics tools may be more suited for specific contexts. Examining the systems employed by competitors can give decision-makers an idea about which tools may be worth investing in.

4. Segment Your Customers Carefully. Some kinds of marketing data can become unusable if they are taken as a whole without considering their context. For that reason, it’s important to divide audiences into segments based on demographics or behavior so that more accurate insights can be gleaned from the data. With better-contextualized data, businesses can then reorganize their marketing efforts more precisely, saving resources while maximizing growth and brand equity.

5. Track Each Customer Segment’s Journey. After identifying key customer segments, businesses must analyze and trace the journeys of each grouping. Learning how customers discover, interact with, and buy from a brand is a good initial test of data analytics capabilities and also provides businesses with insights on how to market to different segments.

6. Start Optimizing Different Marketing Channels. Once a business has solid data on its customers’ buying behaviors, its different marketing channels can be optimized to better suit the specific customer segments that use them. Each channel’s metrics need to be benchmarked and monitored after each set of changes so that marketers have an idea of which tweaks are the most beneficial. For instance, when optimizing an e-commerce site, marketers can look at metrics such as bounce rates, page load times, and conversions to understand how the changes affect the user experience. Similarly, marketers can use social media platforms’ built-in analytics tools to see the utility of different social media campaign approaches. A/B testing can later be used to compare different versions of marketing campaigns and isolate factors that affect success.

7. Implement Predictive Analytics. Once a business’s data analytics infrastructure is built up, it can start experimenting with predictive analytics to forecast future trends and customer behaviors. A properly grounded predictive analytics capability can help decision-makers with long-term marketing campaigns, avoiding risks and preempting customers’ needs.

8. Keep Moving Forward. Customer behaviors are always changing, which means that data analytics is an evolving process that needs to adapt as the market changes. Marketing data has to be periodically reviewed to see if old conclusions hold true and to identify new areas for improvement.

Embracing Data-Driven Marketing

Up until recently, marketing was a field that often had to rely on experience and guesswork, chiefly because the data needed to inform critical operations often wouldn’t be ready in time. Digital transformation has completely upended this norm, turning data analytics from a mere “nice-to-have” into a necessary ingredient of modern, evidence-based marketing. Though each business’s data analytics journey will be different, implementing the best practices above should help any enterprise unlock the full potential of marketing data in driving sustainable growth. (MCN)