Successful big data brands offer actionable solutions.
The premise of big data is that the contemporary datasets of businesses have become so big that alternative methods outside of pure computation must be employed to interpret that information in a timely manner. Oracle, one of the leading technological companies, defines big data as describing a “…holistic information management strategy that includes and integrates many new types of data and data management alongside traditional data.”
In many cases, the elegance and effectiveness of big data solutions that your brand or firm can offer determines its success and reputation. In a globalizing and data-driven marketplace, unique big data branding will rely on convicting premises and striking results.
Educate Your Audience
Big data is a revolutionary field in terms of its breadth and reach into almost every digital transformation we are witnessing today.
Applications and services on phones are often fine-tuned to respond in the moment to customer actions, and big data has numerous benefits in how it can increase brand loyalty, predict consumer purchasing trends, or reveal product reliability. Giving your audience a brief rundown of what big data entails can help ease them into purchasing your service, and education based selling methods are often more effective than plain marketing.
Show How Your Brand Conceptualizes Big Data
There are a few key terms that anyone familiar with big data will be looking out for. Among them are IBM’s breakdown of the four V’s of big data: volume, variety, velocity, and veracity. To establish credibility as a big data brand worth its salt, your firm must provide an extensive and insightful purview of concepts, such as these four values, since it is a signal for competence to your buyers.
Communicate and Frame the Problem of Big Data Effectively
Big data is a problem to be solved, companies are trying to come up with the fastest and most optimal ways to interpret data on a large scale, so how you attempt to deconstruct this complex issue counts greatly towards your brand’s value.
Oracle employs this idea of framing the problem to show their expertise and preparedness incredibly well as they define several categories like business context, architecture vision, current state, governance, and more.
Then they ask a number of essential questions and suggest possible solutions in a chart to indicate the depth of their insight on the topic.
Differentiate Yourself From Other Brands
All big data companies are trying to address this problem of interpretation, and any of your informed clients will understand this business context and landscape. Therefore, you will need to specify and differentiate your brand in order to stand out.
For instance, which area of Cloud-based solutions does your big data brand operate in (IaaS, PaaS, or SaaS) and what is its take on that solution that optimizes the delivery and puts it above other brands?
An article from the Harvard Business Review notes the increasing prevalence and success (80.7%) of big data solutions, meaning that competition between firms will inevitably skyrocket.
Rely on Powerful Visuals to Persuade
Visuals offer transform brands into robust, persuasive vehicles. MIT researchers have found that the human brain can recognize images seen for as little as 13 milliseconds.
Appropriately, using visual methods to make judgments about vast quantities of data is a favored route in some big data solutions. Visuals provide both clarity and intelligence for the client.
Have a Clean User Interface
Clean user interface designs are a detail that any big data company should naturally possess.
You are presenting your user with a program or system that will help them interpret massive amounts of data. If you can’t even manage the information on your site well, how can you expect your clients to trust you to accurately analyze and report on massive amounts of consumer data?
Website navigation and user interface are key aspects of product presentation that you cannot afford to skimp on.
Craft a Tech-Savvy Theme and Persona
Since you are marketing your brand as a big data brand, it is important to maintain an image that you are a company that fluently deals with technological topics and operates at a generally high level of sophistication.
A recent piece in the Harvard Business Review notes that your corporate culture should match your brand: “If your culture and your brand are driven by the same purpose and values and if you weave them together into a single guiding force for your company, you will win the competitive battle for customers and employees.”
Create a Sleek Flow and Perusable Presentation
This point is pretty straightforward and something that even most small firms manage to nail. A sleek flow usually involves a number of pictorial diagrams that interlock with each other and drag the reader in one direction. If you check out any of SAS Analytics’ presentation pages, you’ll note the use of color coding and shapes to demarcate important concepts and enhance the visual impact of information over one page.
Demonstrate the Results of Your Data Analytics Strategy
Show everyone what the general idea behind your big data analytics strategy is as soon as they arrive on the site.
Dazzle them with the promise of unique features if they use your program or if they consult with your business on how to properly approach big data. Mouseflow is an example of a company that harnesses the power of this results-oriented strategy by immediately capturing the reader’s attention with the concept of a heatmap that monitors consumer behavior on a site.
Include Impactful Testimonials and Specific Information
Reputation matters. As a big data brand, you’ll want to piggyback off the reputation of your bigger clients to enhance the perceived reliability of your firm’s own big data strategies. Check out Datameer’s testimonial setup, which includes a clear image of commonly recognizable companies in a clean row of squares. Each of these panels is clickable and leads you to a page with a case study regarding Datameer’s results for that company and the specific targets or metrics of success they employed to measure the impact of their big data solutions.