What's really possible with AI for sales and marketing beyond the hype

(Originally published on OpenView Labs_)_

The hype around AI technology is at all-time high, with the market forecasted to reach $37 billion by 2025_. In sales and marketing, the potential for 10x conversion rates and accelerated growth from AI-driven predictive analytics is enticing. But what’s really possible and what’s still in the distant future?_

Sales and marketing are ranking in the top three markets most heavily affected by the boom in AI investment, according to sources like CB Insights and O’Reilly Media. Industry giants are announcing more AI plays—Salesforce acquiring Metamind and launching Einstein, or Microsoft rolling out Dynamics 365 with AI technologies Cortana, PowerBI, and Azure Machine Learning.

However, there’s a disconnect between what AI can do and what customers and investors expect. Buyers of AI-powered tools aren’t always familiar with the underlying technology, nor do they know which vendors can deliver on promises of accurate and useful predictions.

Predictive Analytics vs Other AI Technology

In sales and marketing, predictive analytics is a type of AI that has gained impressive momentum in recent years. Companies use this technology to predict which leads will become customers based on traits or behavior that indicates their likelihood to buy, then make decisions on how best to pursue those opportunities.

Predictive analytics isn’t the only type of AI used in sales and marketing applications, but it is where a majority of innovation is happening today. Although it’s easy to be enticed by the idea of fully-automated AI workflows or robot virtual assistants that are powered by deep learning and natural language processing (NLP), those technologies aren’t yet ready for implementation on a large scale. Predictive analytics offers tools that work now, making decision-making easier for startup sales and marketing teams who are increasingly inundated with data.

What Predictive Can Do for Sales and Marketing

Predictive analytics helps companies prioritize the use of their sales and marketing resources. For startups, where staying lean and productive is crucial to success, using predictive technology can keep the business growing without hiring new sales reps or increasing the marketing budget. It also increases agility by giving startups feedback quickly, instead of waiting to analyze results months later.

These are some of the best ways for startups to use predictive analytics for sales and marketing:

• Identifying your ideal customer profiles and segments
• Scoring leads based on behavior and fit to prioritize sales efforts
• Keeping your team lean by automating manual activity like research, setting up rules-based workflows and / or updating CRM data
• Integrating data from existing tools to make more accurate predictions
• Targeting customer segments with personalized content and campaigns
• Bolstering account-based strategies
• Moving upmarket and expanding into new territories with promising leads
• Adopting a common, data-driven framework for decision-making

Predictive analytics helps companies hit their growth goals faster without spending substantially more on sales and marketing. But like any extremely-hyped technology, there are several things to watch out for before you buy.

The Human Element: Key Considerations for Startups

Startups and fast-growing companies can use predictive analytics to be far more competitive in their markets, but only if they understand the limitations of AI-driven technology. Human expertise still plays a huge role in how effective a predictive platform will be for your company.

You should be able to answer these questions before investing in a predictive platform:

• Does the software fit your use case? A good predictive platform isn’t built on algorithms alone. It’s created by industry experts who understand how you will actually use it to make business decisions. If a vendor can’t articulate why it fits your company’s use case, it might not be right for your business.

• Does the platform have many integrations? Predictive analytics is far easier to adopt when you can integrate it into the tools you already use, or ones you’re likely to adopt as you grow. Check for open APIs to the most popular CRM and marketing automation tools before you buy.

• Is the vendor transparent about data sources and signals? To trust in a platform’s predictions, you must know why it includes certain signals and not others. Ask about first- and third-party data sources and why the vendor uses them over others.

• Do you have enough data on wins and losses for this tool? In order to build predictive models specifically for you, vendors must be able to train the models with your past sales data. Don’t be pushed into investing too early – waiting a month or even a year to amass more data as you grow might be the right move.

As more companies adopt predictive platforms to help them grow, it’s up to you to decide which technology will keep you competitive. When it comes to AI, there’s a reason for the hype – the potential payoff of embracing it is huge. Stay informed, choose a strong platform and watch your business reap the benefits.

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Director of Outbound Product Management, Google Cloud

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