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How predictive indicators will take Big Data to the next level in 2015

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19th Feb 2015
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Big Data is not a new concept.

Depending on who you ask, the phrase originated in either the 80s or 90s, although it is only in recent years that the term has skyrocketed in popularity. In the marketing and sales realm, every year for at least the past four years has been forecasted as “the year” for big data.

There’s a good reason why Big Data is still a buzzword in this industry: McKinsey & Company found that companies improve their marketing return on investment (ROI) by 15-20% when using big data in their sales and marketing decisions.

However, instead of hypothesising that 2015 is the year of Big Data, I will predict that 2015 is the year that predictive indicators, amongst other factors, such as maintaining updated and segmented data, are helping take data-driven marketing and sales initiatives to the next level.

What are predictive indicators?

Resulting from Big Data and trigger event analysis, predictive indicators are used to derive business intelligence. From a marketing and sales perspective, they indicate the likelihood of someone purchasing your product or service. While typically, data-driven marketing and sales meant using basic demographics (or firmographics in business-to-business settings), predictive indicators look at these metrics along with other variables, such as job changes or a relocation to a new region of the country.

These triggers can signal that it is the perfect time to contact a particular prospect to offer a solution to meet his current needs. With indicators that become smarter over time by analysing past occurrences, sales representatives and marketers know exactly on which prospects their efforts should focus, thereby reducing wasted time and increasing efficiency.

Making triggers predictive

But how do you track triggers and make them predictive? Given the deluge of data that is available about almost anyone or anything, it can seem like a daunting task to try to keep up with each prospect your company wants to target. Managing data and turning it into insights has been a constant struggle for just about every function within organizations across industries.

For example, if you are a sales representative working in a recruiting company, your target market could potentially be huge. Instead of going after every company in your region, you need a way to target the companies most likely to enlist your services – those companies that just reported increased revenue, are actively hiring or are opening a new location. This could take hours of research and combing through search engines, social media, local directories and news media.

To alleviate this burden, companies can adopt predictive tools that do the legwork for them to track the signals that are most important to the organization’s selling and marketing function. The wealth of information available in Big Data can only be unleashed by tools that will simplify search. Instead of culling through every piece of information available on a prospect, new tools and technology make it possible to hone in on the one nugget of information that will make a difference for your sales or marketing team.

Once you’ve identified the ideal prospect to dedicate your time and energy, predictive indicators used in real time can further enhance your efforts. Data will help you move beyond a general sales pitch where you talk all about yourself and what you have to offer. Instead, armed with real-time data about what your prospect is going through at this particular moment, you can shift the conversation from a sales pitch to a more strategic discussion about your understanding of the prospect’s challenges and how you will help to address and alleviate them.

What’s more, real-time analytics increase the chances of you striking up the conversation with the right contact at the right time – during a compelling event. For example, a newly appointed CIO is a trigger that sales reps should identify. This is because someone coming into this position makes an average of $1 million in buying decisions within her first 90 days on the job. Sales people want to be the first to identify this opportunity in order to capitalize on it.

Additionally, many buying decisions are based on intolerance to the product or service already in place. Until the current solution is no longer bearable, most people will stick with it and maintain the status quo. Why fix what isn’t broken? Why spend money when you don’t have to? These are questions that sales and marketing representatives have to be prepared to address with prospects. By identifying a prospect’s individual trigger points and understanding the challenges with his current solution, a sales rep can get a prospect off of the sidelines and ready to make a buying decision.

With predictive indicators, sales and marketing teams can perfect their timing to identify unique selling opportunities with individual prospects, providing them with the right solution for their current needs and improving the likelihood of cold calls converting into leads or sales. In 2015, the organisations that fail to use predictive tools will find themselves left out in the cold as competitors move quickly to identify the best prospects, have the right conversations and close deals.

Victoria Godfrey is the chief marketing officer of Avention. Prior to joining Avention, she spent five years running her own marketing and research company, Godfrey Research. 

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