The amount of consumer data that’s readily available nowadays is enormous. Turning this into large-scale analytics, or big data as it has become known, has endless business benefits.
The value in big data has been apparent for many years. However, the concept has only recently taken off thanks to rapid advancements in technology.
Our expert in the field, author Alex Lysak, believes it’s time for entrepreneurs to learn how to implement it into their business models. Improper use or focus in the wrong areas can lead to significant problems with big data analytics.
Data Is the Key to Your Customers
Big data reveals patterns in the information you receive through web traffic, marketing campaigns, and behaviors. These insights open up unprecedented opportunities to understand your consumers better.
Without any analytics, online companies are unable to identify positives and negatives. With big data, business owners can make informed conclusions. In return, these discoveries help to shape future decisions and direct campaigns.
Types of Analytics at the Core of Big Data
Analytics at this level can give you an insight into just about every area you’d wish to know. However, at the core of big data sits four main areas that can have the most impact on your success.
Demographics consist of data such as age, gender, and location of your customers. It’s crucial for understanding what audiences are creating clicks, leads, and sales. You can then tailor your marketing and SEO to strengthen this traffic or redesign to cast a broader net.
Companies like Scanteam work with clients worldwide. As a result, they’ll rely heavily on demographic analysis to better understand what works in specific parts of the world.
You can track the success of your content by evaluating what is driving visitors through the sales funnel. On the other hand, you can also notice areas that are halting the progression of leads. By doing this, you can adjust your site accordingly.
Back in the day, to see if your latest advertising campaigns were a success, you’d have to wait for customers to walk through the door. Online business results are much faster. Additionally, with analytics, you can measure a campaign’s success with performance statistics. For instance, you can view clicks per minute, clicks that generate leads, and compare campaigns in different areas.
This type of data enables cross-referencing of an array of information to find insights into consumer behavior. For example, you could find that a specific demographic enjoys certain content at a particular time of the year.
Big Problems in Big Data
Digital marketing and big data analytics often don’t yield the results business owners expect. As previously mentioned, this is often due to their understanding of the concept. Often energy is put into the wrong areas. Moreover, beyond this, information isn’t tested for accuracy or quality.
For instance, many companies fail to update their client base regularly. Current information like their email, phone number, and address are critical pieces of data. If customer contact credentials are incorrect, then any insights you find based on this will be inaccurate.
Furthermore, large companies will have a broader client base. As a result, they’ll often harvest a considerable amount of data and struggle to keep up with maintenance and management.
The sheer volume means more work is needed to organize it. Therefore, less time is spent using it to extract insights. Additionally, much of it will become outdated and invalid by the time anything meaningful can be used for big data marketing.
Using bad or ‘dirty’ data analytics for marketing can result in many negatives for your company, which you should avoid. These include:
- Negative reviews impacting word of mouth
- Failure to reach audiences through advertising campaigns
- An increase in spam leading to customers unsubscribing
- A complete distortion of your metrics, resulting in an untrustworthy success rates
- Product delivery, personalized emails, and call mistakes
- General customer dissatisfaction
Applying Effective Solutions
Circumnavigating big data, both effectively and solo, is going to be a challenge. A small company may be able to juggle it but at a cost to time. Your primary focus should be to evaluate the accuracy and update the information in your storage.
You’ll need to eradicate any inaccuracies or void information systematically. Moreover, conducting follow-ups with clients will not only draw them back for repeat visits but also ensure your data is correct. In return for this effort, you’ll build a foundation for the new information you harvest and gain productive insights.
Thankfully, there’s a myriad of tools available to help you. As your business grows, you can outsource the responsibility by hiring a big data analyst or architect. However, finding skilled workers specialized in the field is hard to come by.
As mentioned previously, this type of data collection isn’t a new idea, but its application is. Thus, only a small pool of specialists are available, and their services are highly sought after. It may be more beneficial to develop a team of analysts by re-training current employees. Alternatively, you could recruit outside analysts interested in specializing under your employment.
Using analytics is key to understanding your customer’s wants and needs. Big data can give you valuable insights into what is working and failing in numerous areas of your business. You can then cross-reference these patterns for long term goals and advertising. If utilized effectively, it can keep you one step ahead of the competition and ensure your venture thrives.
However, there’s an evident discrepancy between understanding its value and the knowledge surrounding how to use it for the best outcomes. The majority of problems with big data are born from the scale of information companies receive and the inability to employ strict quality and accuracy measures.
Using tools, creating a dedicated analytics team, or hiring experts is the best solution. By doing this, you’ll ensure that what you collect won’t end up useless due to inaccuracy.
Small companies may feel on a back foot when it comes to big data. If you’re starting out, don’t be discouraged by the volume of information you receive. In fact, it’s far easier for you to manage and maintain. Finding useful insights will be quicker, and there’ll be fewer chances of dirty data corrupting your metrics.