Running a small business is one of the most rewarding jobs on the market. It takes a lot of resilience and persistence, especially when it comes to building flexible marketing campaigns that are both impactful and cost-effective. Digital marketing and the technology that comes along with it are some of the best tools small business owners can wield in both establishing an audience and targeting new customers. This article will explore the key technology used in data analytics and how it is used to help digital marketing professionals elevate smaller businesses.
Data storage and management systems
When you think about digital marketing, what comes to mind? For many, the answer is some kind of advertising campaign or social media platform. Both of these are, of course, incredibly important to the industry, but they aren’t necessarily the most important element of digital marketing. You might not immediately think of data storage, but the truth is that storage is just as important to an effective digital marketing plan as email campaigns and advertisements. More specifically, data storage and management systems are crucial in marketing plans running smoothly and targeting the appropriate communities.
One of the biggest benefits data storage and management systems offer digital marketing is the ability to collect information about customer demographics, behaviors, and preferences. Data storage and management systems make it easy to record and analyze raw data. Businesses can then create personalized marketing campaigns designed with a specific audience in mind. If the data shows that a target audience rarely responds to traditional email marketing campaigns but is always on their mobile devices, for example, marketing techniques that rely on mobile software might be the most effective.
If your goal is to grow your small business with digital marketing, your first step should be to secure and implement a robust data storage and management system. This forms the foundation upon which future marketing strategies are built.
Data processing frameworks
We know that data is important to marketing, but storing data and performing quick analyses isn’t the only way to use it. Making use of processing frameworks to perform deep analyses and interpretations of large quantities of data is the backbone of digital marketing. Also known as “big data frameworks”, data processing frameworks are tools that make analyzing raw data securely, effectively, and rapidly straightforward. They offer users enhanced organization and present smaller businesses with a foundation upon which their data is collected, structured, and used. Perhaps more importantly, data processing frameworks give small business owners and managers an easy way to integrate raw data, or “big data”, into their everyday decision-making.
You might wonder how much an effective data processing framework will set you back. The good news is that most of them are open-source, which means they are free. It is possible to take existing code, modify it for your needs, and build the perfect system without paying a dime. If you don’t have the expertise needed to problem-solve potential problems, you can always purchase support. When you buy support, you can decide how much money you want to spend on data processing framework initiatives and avoid dedicated data management employees.
The proper data processing framework elevates smaller businesses by improving the accuracy of their data interpretation. As a result, businesses are able to make better decisions based on deep data processing interpretations.
Data integration tools
Recognizing how data analytics help business and implementing it into daily operations are completely different processes. The former is something that most people can appreciate, but the latter requires time, dedication, and skill. Studying a reputable online degree at St. Bonaventure will ensure you stand in good stead to work in high-responsibility roles in data analytics. The Master of Science in Business Analytics program can be completed entirely online and in as little as two years. This program ensures students can integrate data into daily workflow and refer to the process of harmonizing and combining data acquired from multiple systems, formats, or sources into a single source of truth. Proper data integration makes it easier to utilize data when making decisions, but the integration process can be an overwhelming one. That’s where data integration tools come in.
Data integration tools are designed to automate the process of making data part of an employee’s daily workflow. With easy access to data analysis comes more accurate and productive decisions that help optimize growth and maximize efficiency. Data integration tools include extract, transform, and load (ETL) tools, data preparation tools, data migration tools, and data integration platforms. Any of these can help you integrate data into your business, although the perfect choices depend heavily on your business and your goals.
Data visualization platforms
So far, we’ve talked about how data can be used in digital marketing to help businesses grow, but we haven’t talked about the process of interpreting data as the end user. It is one thing for data scientists to take stock of a certain data set and quite another for business owners or managers to understand what big data is telling them. Data visualization platforms are an ideal solution to this challenge.
Data visualization refers to the process of taking raw data and turning it into a visual graph, infographic, chart, or other visual graphic. This makes the data much easier to understand. It becomes “usable”, allowing business owners and managers to make accurate decisions based on the data in question, rather than a mass of seemingly incomprehensible raw numbers. If your goal is to use data to grow your small business, you should utilize data visualization platforms to build a digital marketing campaign that is perfectly suited for your audience.
Machine learning and predictive analytics
The most effective digital marketing campaigns are those tailored to your customers. This includes offering personalized user experiences for consumers at different stages in the sales funnel. Returning customers require different marketing strategies than potential first-time customers, for example, and data can help you determine the way customers are using your service or product, how they are interacting with your company, and how different promotions and marketing strategies might impact their behavior.
Machine learning and predictive analytics collect and analyze the data necessary to offer a truly personalized experience to customers. This includes key performance indicators (KPIs) such as lifetime customer value, product recommendations, marketing attribution, and marketing effectiveness and ROI.
Both machine learning and predictive analytics use past information to construe current and future trends. Digital marketing uses information about these trends (and potential trends) to build customizable marketing experiences for your users and, potentially, grow your business.
Statistical analysis systems
For a campaign to be successful, it must be closely focused on the proper target audience. Statistics are used to evaluate and measure marketing programs, identify market trends, and assess the effectiveness of marketing campaigns and objectives for very specific groups of customers. Some of the most useful statistics to use in digital marketing include social media engagement, site traffic, click-through rate (CTR), and return on ad spend (ROAS).
Up to this point, we’ve talked about how key technology can help digital marketing professionals develop the kinds of marketing that yield business growth, but we haven’t talked about revising plans to improve their effectiveness. You must be able to measure a campaign’s impact. All of the above are used to measure the overall success of the program in question and provide valuable information about the target audience and their marketing preferences.
Statistical analysis systems, in particular, are used to interpret raw data and produce information that is both easily interpreted and useful to a digital marketing team. Through trial and error, marketing professionals can craft highly targeted and precise campaigns that get significant results.
Cloud computing platforms
Cloud computing is a common concept. There are three main aspects of cloud computing to understand. They are cloud storage, cloud computing services, and cloud computing applications.
Cloud storage, of course, refers to sharing and storing data online so that employees can easily access it as the need arises. Cloud computing services are cloud-based technologies such as cloud hosting, cloud analytics, cloud security, and cloud computing security. Cloud computing applications refer to cloud-based applications that help businesses manage their operations as cost-effectively and efficiently as possible.
Cloud computing has changed the way that businesses of all sizes operate for the better. It encourages collaboration and makes it easier for professionals to work while on the go, reducing the use of sick time and cutting down on the costs associated with it. As it pertains to digital marketing, in particular, cloud computing grants marketing professionals faster access to data, improved analytics, deeper data insights, mobile accessibility, and cost-effective solutions that don’t require costly investments in hardware.
Natural language processing (NLP)
Natural language processing (NLP) is a field of computer science closely related to artificial intelligence. Its main focus is the development of computers that are able to summarize, translate, and read the text and understand its context like humans do. This includes nuances such as regional accents (when analyzing audio speech), misspellings, informal terms, and slang, among others. The ultimate goal is to enable computers to understand human language and train them to respond accordingly. If you’ve ever used a chatbot, for example, and been either frustrated because it doesn’t understand or impressed because it does, you’ve experienced the handiwork of NLP.
Through the use of NLP, digital marketers can help promote business growth in a few different ways. First, it can dramatically reduce response time to customers, giving them the information they need to make an informed decision to purchase your product or service. You don’t have to worry about losing a customer to a competitor because you didn’t get to their message or email soon enough, in other words. NLP can also be used to analyze the sentiments of your audience. By looking at the kind of language used when referring to your business, social listening tools with advanced NLP help marketers better understand your brand image.
NLP can also be used to improve audience reach and boost SEO rankings, as well as in content generation and customer service. It is used to expand audience reach by analyzing data from multiple platforms and allowing marketers to direct relevant ads to their users. The technology can help boost SEO rankings by analyzing the market and pulling the most commonly used and most effective search tools for use by marketing. It helps determine gaps in your content, too, as well as interact directly with customers to solve simple problems.
The power of data analytics in digital marketing
Digital marketing increasingly relies on key data analytics technology to develop, implement, and refine marketing strategies. From identifying potential customers to analyzing their behavior and purchase habits, data analytics is the perfect complement to effective marketing professionals. Are you interested in learning more about emerging technology related to digital marketing? Use the above as a springboard to help you conduct more specialized research into your areas of interest.
