It’s no secret that strong data analytics is at the core of any successful marketing strategy. Beyond that though, data analysis is key for generating the insights that drive decision making and spending. So, what exactly is data analytics and how can DTC advertisers use it?
Over the last few years, direct to consumer (DTC) brands have been on the rise. By removing the third-party resellers’ middlemen, DTC business models have profited from controlling their value chain and owning the customer relationship. DTC brands are able to collect a variety of data from their customers, including behavioral, transactional, and demographic data.
What is data analytics?
Data analytics is the process of studying data sets to determine trends and identify important indicators. After this analysis, you can draw conclusions about what these trends and indicators mean for your business. Essentially, data analytics in marketing analyzes raw data. This leads to conclusions about different information to understand the algorithm for customer consumption.
Customers can be analyzed based on their attitudes and demographics. This makes the data more accurate and specific based on customer interest. Having a clear understanding of data analytics and its effectiveness in DTC advertising gives businesses the right trajectory to maintain customer satisfaction.
How analytics are used in marketing
Marketers use data analytics to pinpoint campaign patterns and see how campaigns contribute to conversions, consumer behavior, sales, and more. It also helps marketers consolidate data from multiple sources by eliminating ineffective advertising strategies. Other benefits include managing risks and detecting irregularities that could be indicative of ad fraud.
What are the benefits of data analytics?
Using data analytics has countless benefits for businesses. It helps them understand their customers by making informed and data-driven decisions, which is why many brands prefer DTC marketing. According to research by Villanova University, the global digital advertising market reached $153.65B. It was predicted to reach $260.36B, but it increased even more due to the pandemic.
It also helps marketers consolidate data from multiple sources by eliminating ineffective advertising strategies. Other benefits include managing risks and ad frauds to analyzing operations and detecting irregularities. Moreover, delivering a well-optimized and personalized customer experience not only ensures business success but also increases customer satisfaction. This makes them opt for your company every time.
However, as more data is being gathered than ever before, analyzing it effectively and drawing accurate conclusions is increasingly challenging. Having a clear understanding of data analytics gives businesses the right trajectory to maintain customer satisfaction.
Here are a few tips on how DTC advertisers successfully can use data analytics in advertising:
9 Ways DTC Advertisers Can Use Data Analytics in Advertising
1. Understand the Targeted Audience:
Even when brands choose DTC advertising, understanding their audience and consumers makes all the difference. Taking the time to understand the target audience and their interests is an essential initial step as it reduces ad fraud and encourages effective ad costs. In addition to demographics, first-party data can also give insights into further information, including usage, likes, dislikes, etc. Through this, audiences can be segmented into different categories, who can then be shown advertisements based on their interests.
Without understanding the right audience, advertisers can lose a tremendous amount of money. This can make you lose your money and decrease the chances of reaching the right audience. When the audience is chosen according to their interests, the data can be further optimized and personalized to ensure they revisit your brand. BDEX helps marketers like yourself understand and target the right audience, which will increase your advertising success.
2. Audience Segmentation:
Data analytics helps companies understand how to segment their audience based on their specific behaviors and needs. Not only do customized segments help marketers create personal customer connections, but they also serve as effective tools throughout the sales process. Through segmenting, advertisers can better understand what drives certain customers to make purchases. Once you have this knowledge, you can personalize messaging to segmented groups to increase conversion rates and build customer retention. Content that is relevant and relatable will always be appealing to new audiences and customers.
3. Advanced Personalization:
Marketers should use the collected audience data to make consumers regular customers once they have visited your site through an advertisement. A marketer’s job does not end when an ad brings customers to your website.You also have to keep the consumer engaged while they are on your brand’s website to increase their chances of making more purchases, which will in turn help you learn more about their purchasing behavior.
4. High Quality Content:
With the knowledge and understanding of the targeted audience, it gets easier for DTC advertisers to produce relevant, high-quality content. Audiences and customers are always attracted to brands that keep investing in their advertisements. As a DTC brand, you will already know what interests your consumers, so that data should be used to make attractive advertisements for regular and new customers. High-quality content in the current times can include anything from YouTube videos and trendy Tiktok’s to creative Instagram posts.
5. Long-term Engagement Using Data:
The purpose of opting for DTC advertisement is to ensure customer loyalty, which can be gained through a long-term engagement. DTC advertisers can present the customer’s optimized data through email promotions, loyalty programs, and different online subscriptions. Businesses will be able to find out the customer’s buying habits and frequency through their data, targeting the right audience. Through data analysis, DTC advertisers can show them related products that are personalized to ensure long-term engagement.
Another way of using data analytics for long-term engagement is the creation of different personas. This is an advanced way of optimizing data to categorize specific people into groups for better engagement and reach. For these people, DTC advertisers need to use the acquired data to match their categories to meet their needs.
6. Cross Channel Attribution:
Similar to how data analytics is a key tool in understanding whom to contact, it also can be utilized to determine the right platform for customer outreach. This can be accomplished with cross-channel attribution. Cross-channel attribution recognizes the channels that are the most impactful for customers and provide the highest ROI. Whether it be social media, email, or SEO, data analytics helps advertisers identify the platforms that complement and work together with their overall marketing strategy. This helps ensure that marketers are reaching consumers on the channels that hold the most value to them.
7. Predictive Analysis:
Together with audience segmentation and cross channel attribution, predictive analysis is critical to sales conversions. By combining data analytics tools with AI-powered predictive algorithms, you can anticipate how customers will act in the future. When used with consumer behavioral data, predictive analysis can help brands maintain engagement with potential customers, anticipating their wants and needs. Overall, this leads to better optimized marketing campaigns and helps build customer loyalty.
8. Keyword Optimization:
To really understand your audience, it’s important to first know how consumers find information online. Data analytics lets advertisers know what keywords consumers are searching for when looking for products and services. Once you have this keyword list built, you can target audiences with those specific keywords on social media and online to drive traffic.
9. Investing in New Customer Acquisition:
DTC advertisers have a well-defined target audience, making it easier for them to attract new customers. content and advertisements that are attention grabbing should be linked directly to your website making the user experience smoother and leading to profitable marketing. Advanced audience targeting will allow your DTC brand to spend money more efficiently.
First impressions matter, so exceptional customer service will attract new consumers, along with advertising using data analytics. You can pitch your products to different consumers through your chat service based on data analytics. Moreover, you can build brand loyalty through an effective email marketing strategy. Using the data of people who share your customers’ interests is also an effective way for DTC brands to use the collected data.
As a result of COVID-19, Consumers have started preferring online shopping over physical purchasing, giving DTC advertisers the chance to strengthen their online presence. Using the mentioned strategies, DTC brands can take advantage of these shifting purchasing habits to build a loyal customer base through data analytics.
Data is valuable, but advertisers can only realize its value if they have the right tools to extract data insights. To turn their data into profit, advertisers should utilize data analytics to build custom audience segments. They can also identify their top platforms, predict customer behavior, and optimize targeted keywords. As advertisers prepare to enter the post-cookie world, it’s more important than ever to ensure they’re maximizing their data’s full potential.