As the need for big data grows, so does the need to tell consumers just what it is and how to establish buy-in and trust. Not only does this stand true for the consumers, but there is often some pushback from internal staff. Sometimes they feel that big data has already been put in a bad light, so why add additional negative publicity for the company? Other times, you get push back from IT, as they don’t really understand how to market it, they only know how to implement it. This makes it hard to get some understanding so that it can be marketed properly. So, this begs the question—with this new onset of glamourous data that can be manipulated and used in so many ways, how do you market it effectively, and how do you communicate the message to the sales team so that it can generate revenue and contribute to the company’s bottom line?
Ensure the Software Does What It Says
When developing software, requirements should be developed in the earlier stages of the project that define how the product should function. In the case of big data software, it should perform in the way of satisfying its purpose to the masses—providing a wealth of information that can be explored with a simple query or click of a button. Big data is so popular these days that companies expect this as a minimum. To win them over, more has to be done—can they use the data to create their own applications or use the tool to make decisions that will appeal to other industries other than their own? Having these requirements mapped out from the start of discussions will make creating a marketing plan that much easier, as you can build it parallel to the development team building the solution. In addition, this makes it easier to uncover flaws in the development, as utilizing research to uncover trends will undoubtedly cause the scope of the project to change.
What You’ll Need First
In order to make a big splash with marketing plan, define an effective yet thorough go-to-market strategy. This is “a tactical action plan that outlines the steps necessary to succeed in a new market or with a new customer. It can apply to pretty much anything, from launching new products and services, to re-launching your company or brand, or even moving a current product into a new market.” A go-to-market strategy is enough to not only gain market share but to increase profitability. Therefore, the plan should be enough to draw in a crowd of buyers that your software will entice with features like out-of-the-box implantation, meaning that the they won’t have to do anything but implement it into their current network. This eases the minds of those in the C-suite, which helps to assure them that you can use the product sooner rather than later, i.e. having to convert it into a project that could take weeks or months to implement.
The Easiest Selling Point
The easiest way to a marketer’s heart? The ability to use the tool in their current marketing technology stack. For example, if an email marketing solution is already being used, your big data solution should be able to communicate and unveil other metrics that the company can utilize; for example, the ability to distribute more personalized emails with robust factors, like the day of the week they’re most active on social media, music that they enjoy on Monday mornings, etc. Those are key personalization factors! Campaignmonitor says that “74% of marketers say targeted personalization increases customer engagement, and they see an average increase of 20% in sales when using personalized experiences.
Seeing the Whole Story
When integrating all the marketing technology that you have available, it creates a digital ecosystem that cannot be touched! Your email will communicate with the web, the web will communicate with the data, and the data will connect everything! This way, users are given a personalized experience that your company can take full advantage of. For example, being able to use a customer’s first name throughout all marketing communication will help the customer feel as though they are a part of the company, rather than just a number.
What a marketing plan can do for big data
With big data meaning so much to so many, just the mere fact that a company is utilizing it is a sale all by itself. It can “enable psychological segmentation.” Here, machine learning algorithms can apply to target customers with relevant personality traits. Content and ads can tailor to the customer’s preferences, increasing the conversion rate dramatically.”
Marketing holds all the cards
Because it is the marketer’s job to get the word out, “the role of big data for marketing teams is huge. When developing a campaign, it is critical that every marketing specialist first understands several variables, like the target audience, your opponents’ strategies, etc. And, this is exactly what big data helps them do.”
To sell big data, companies must:
- Sell big data using an outside-in approach. That would entail understanding the business challenges and vision of the specific business first and then and making a determination if big data can indeed meet their challenges. Every business challenge might not need the application of big data solutions and this determination is very important before starting anything further.
- Decompose the business challenges and vision statements into relevant business use cases and vet these use cases with business leaders and personnel to determine if they generate any interest in the community. Also determine if the existing business cases can be partially or fully met using existing analytics investments.
- Once the business use cases have been determined and prioritized, bring in industry domain knowledge and mathematical experts to determine if these use cases can be addressed using business knowledge coupled with the application of known or custom modelling techniques. The outcome of this step should be a business solution with machine learning and statistical modelling techniques embedded into it.
- After completion of the previous step, feed the business solution to the technical team. Employ big data technical architects to conceptualize the customer landscape, select big data tools and design the technical integration to technically support the business solutions. I would recommend the use of open source tools to keep costs in control and design a scalable architecture.
- The outcome of the above steps must be data or artifacts that directly address the challenges of the business use cases and the proposed solutions must collectively drive towards meeting the business vision of the organization
- As a last step, sell the business solution of the business leaders first, and then drill down into the how the business solution was arrived at showcasing the domain and statistical modelling techniques that went into it, finally concluding with a detailed description of the architectural landscape that would host these business solutions. To further justify the need for the bid data investment, as part of the technical piece also elaborate why the proposed solutions cannot be met with the business’s existing analytics investments.
- For repeat business and expanding your big data footprint by adding additional use cases, go back to step one
To overcome the challenges of selling big data, marketers must understand all facets of big data analysis. In order to succeed, they must “define what they want to get from their big data analysis. Then, they can churn out valuable insights based on needs and requirements. An intelligent big data strategy will help marketing experts make more effective plans.”
Consumers have come to demand and expect relevant and personalized content and experience, both online and offline.
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