Predictive Data Analytics is the process of using historical and current data combined with machine learning to forecast certain outcomes. In the marketing world, predictive analytics uses monitoring and reporting to accurately plan strategies and campaigns. For nearly a decade, this type of marketing research has been changing the landscape of how organisations reach and impact their audiences.
Find better leads
Using the historical data of both a certain company and the industry a company is in, certain factors pertaining to sales leads can be found using Predictive Analytics. For instance, a financial advisory firm may find that individuals between the ages of 52 and 58 who exhibit certain behaviours on social media are significantly more likely to become clients.
Such indicators can be used in a number of ways including:
- Ad targeting
- Suggestive copywriting
- Lead prospecting
- Targeted sales conversations
Identify prospects faster
Many companies employ the use of a customer relationship management software (CRM). These tools typically include a way to score leads. Scoring is simply a numbering system to alert the marketing and sales team when a lead is close to making a decision. When this data is combined with machine learning and artificial intelligence, identifying sales-qualified leads becomes easier over time. Moreover, predictive analytics can be used to shorten the sales cycle by better predicting a leads behaviour when in the funnel.
When the process of identifying sales-qualified leads (SQLs) is done manually, there are many mistakes that can occur. For instance, if a lead downloads a certain resource it could trigger the marketing team to send that lead to sales. However, predictive analytics may tell you that a lead may have downloaded it too quickly and is not ready for a sales conversation.
Better align sales and marketing
Try as they might to understand one another, the marketing team and sales team have very different roles. More often than not, this results in a breakdown in communication that can cost a company revenue. The nature of predictive analytics is to improve over time. Data from both the sales and marketing team can improve multiple factors including:
- Handing off leads
- Communication of promotions (e.g. discounts)
- CRM implementation and updating
- Quality of leads in the funnel
Understand current customers
Many organisations rely on customer retention and add-on sales over the course of time. Retail banks, software-as-a-service companies, financial advisors and many others rely on customers sticking around for a long time. Predictive analytics helps to understand not only leads and new customers, but also the behaviours of existing clients. These factors influence marketing in a number of ways.
- Lead Generation: Certain leads may be easier to close than others. However, if those prospects end up leaving before they become profitable it won’t matter. By understanding the behaviours and attributes of clients, you can better target your lead generation efforts and acquire better long-term customers.
- New Products/Services: Predictive analytics can listen to your current client base. The data collected can be used to improve current products or even create new offers tailored specifically to predicted needs.
- Improve Referrals: Asking for referrals is an important part of any company’s lead generation. However, timing is often times unpredictable. With past behaviour and predictive analytics, understanding exactly when a customer is ready to refer you can be achieved.
Perhaps one of the most impactful ways predictive analytics will reshape the marketing world will be through automation. Once the behaviours of lucrative prospects are identified, sophisticated programs can interact with leads almost immediately.
Here are a few examples:
- A lead, who fits your buyer profile, tweets a keyword pertaining to your business. A software program automatically engages with that tweet from your Twitter account.
- A prospect comes to your website through organic search and your webpage offers a resource tailored to that specific user based upon their search criteria.
- Current leads in the funnel are monitored for social activity pertaining to your industry. Once certain behaviours occur your sales team is notified.
Better budget allocation
Improved understanding of who your buyers are, where you can find them and the resources to use to garner interest can all dramatically decrease ad spend waste. Overtime, predictive analytics can alert the marketing team to platforms (i.e., Facebook, AdWords) that are less effective as well as methods (i.e., video, cold email) that are not as likely to work. Conversely, the same predictions can be used to increase spending where efforts are likely to achieve the desired results.
Predictive data analytics is quickly becoming the driving force behind modern marketing. From drastically improving lead qualification to better aligning sales and marketing initiatives and making targeted marketing automation more in-tune with customers’ needs in-the-moment, predictive data analytics amplifies the ability to cater to individual customers – and that’s the magic formula for success in the modern marketing landscape.
Taj Nota, VP Professional Services UK, NGDATA
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