With so many options at the modern marketer’s fingertips – email campaigns, sponsorship, social media posts, content creation, influencer marketing, and more – it’s not surprising that we can sometimes feel paralyzed, not knowing which option is the best for which audience at which time. Decision intelligence is urgently required yet sorely lacking.
Most modern marketers face two forms of bewilderment: choice paralysis and decision paralysis.
Choice paralysis (also known as over choice) is when too many options are presented and there’s no straightforward way to decide between them.
Decision paralysis is when there may only be two or three options, but you have insufficient data to choose between them.
We all encounter this in our daily lives at the supermarket or when selecting a new cell contract, but there’s no reason to face either in marketing. This is where data (or decision) intelligence and decision intelligence platforms come into play. They help businesses replace hunches with certainty.
What Is a Decision Intelligence Platform?
A decision intelligence platform is a type of software platform that integrates many data sources and enables marketers to make the right decision at the right time. It does this by providing marketers with fewer but better choices, circumventing the potential for both types of mental paralysis.
To appreciate how it works, first we must accept that sales and marketing functions are inextricably linked. Although one may be considered more creative (marketing) and the other more persuasive (sales), they are both essential approaches to the art of getting your product or service in front of the right customers at the perfect moment.
Data Intelligence pulls in information from both marketing and sales sources, telling us both how people feel about our product, what behavior they exhibit towards it, and most importantly, which marketing activities are impacting revenue. These subtle behavioral insights can be gleaned from raw metrics. Consider, for instance, the following data sources and what they tell us:
|DATA SOURCE||INFORMATION TYPE|
|Subscriber Churn||Level of satisfaction with product/degree of product fit|
|Consumer Star Ratings||Sentiment analysis – common likes and dislikes|
|Time Spent on Landing Page||Content quality, interest level|
|Social Media Shares||Popularity of brand message|
|Abandoned Shopping Cart Data||Barriers to purchase / possible pricing issues|
|Product Demo Conversions||Possible product or pricing issues/degree of product fit|
However, even concrete numerical data like demo conversions can relate to several potential causes. If there aren’t enough conversions, is this because the product has flaws, it’s overpriced, or the wrong potential customers are being targeted? We need to cross-reference and correlate a host of different data sources to zero in on the true reasons for any problem.
The trouble is that such investigations take time and are prone to natural biases. If you wrote or approved the landing page copy, it may be hard to admit that perhaps that copy is failing to deliver the predicted number of product demo requests.
Data intelligence and decision intelligence platforms go further than simply handing us digestible chunks of data. They perform these correlations and use them to offer prescriptive solutions – next best actions per campaign, per audience, per product, etc.
How does AI Inform Decision and Data Intelligence?
A decision intelligence platform takes data analytics one step further than merely deriving conclusions from raw data at scale. It models the whole decision-making chain, analyzing what actions most frequently produce the right outcome in any given situation.
Like any platform using AI, the algorithms must first be trained on a pool of sample information, including data on what human decisions were made and the outcomes. Depicted visually, the machine learning process looks like this:
The AI pulls in all of these data sources and starts to recognize patterns – tried and tested strategies that can be adopted in response to changes in the environment, which includes everything from the health of the market in general to the pressure of competition, the state of the economy, technological and other factors.
Ideally, the decision intelligence platform will generate a few best choices and recommendations for what actions to take to achieve the intended outcome or move the buyer through the sales funnel faster. It may even allocate a predicted percentage of success rate or generate a chain of actions to be taken at critical intervals, depending on how sophisticated you want the AI’s decision-making to be.
This means marketers are no longer operating on guesswork or gut instinct alone. Now their decisions can be informed with reliable data – here’s what has worked before, and you have good reason to suspect it will work again.
The Advantages of Adopting Decision Intelligence Platforms
There are many good reasons to adopt a more data-driven approach to decision making:
- It reduces guesswork and improves the chance of success
- It limits choice paralysis by narrowing down the possibilities
- It recommends strongly viable options but leaves the final decision up to you
- It helps marketers justify the creative expenditure
- It shapes helpful priorities for sales teams
- It allows you to justify your actions when things don’t work out
The last point is important. Although decision intelligence platforms perform far better than even the most experienced marketing professional, they don’t get everything right. There will always be outliers and unpredictable events which throw spanners into the works – supply chain issues, global pandemics, political upheaval, and economic fluctuations.
However, marketers and sales professionals will always be able to give a reason, backed up by data, for their choices.
7 Steps to Optimize and Implement a Decision Intelligence Approach
There are a series of steps to take before you can get the most out of any decision intelligence platform:
1. Choose the right decision intelligence platform.
2. Ensure your data is complete, accurate, optimized, and available.
3. Make sure you have sufficient data to train the platform’s AI – ideally going back several years.
4. Make sure your integrations are working properly, using a customized integration solution over a native integration that may not connect to every system or allow you to pick and choose the data you want to pull and where you want it to go.
5. Test the software on a set of data and customize the platform to supply the information your marketing and sales teams will find most helpful.
6. Ensure staff are trained in the platform’s purpose and have bought into using it for the right reasons.
7. Begin monitoring the platform’s usefulness and performance and adjust any parameters you might need to as time passes, adding new data sources and integrations when they become available.
A good decision intelligence platform will provide you with all the support you need to implement their product effectively in a way that delights your marketing and sales pros.
Use Cases: Decision Analytics for Reasoned Choice Making Every Day
Select a decision intelligence platform that has been designed to inform your decisions and present clear courses of action with a real impact on revenue. Here are some examples of the ways it can help your marketing and sales team in their day-to-day work:
Decision Intelligence in Marketing
- A content manager wants to know how frequently to commission articles, of what length, and when they should be posted on the brand’s blog page. Their decision intelligence platform tells them that 1500-word pieces posted weekly on a Monday afternoon perform better than any other. This is implemented as policy and results in a boost in product demo requests.
- A marketing assistant needs to set up a five-email drip campaign but wants to know how to space and time their messages. The most effective timeframes are specified by the decision intelligence platform and automated so that each customer is served the next part of the campaign at the optimal moment.
- A brand manager is targeting a much younger demographic for a new product. The decision intelligence platform reveals that TikTok videos and Instagram posts hit that demographic much more effectively than any other social media channel. The manager decides to commission an influencer campaign for both platforms.
The platform can also tell the marketer when to implement multiple tactics for the same campaign. For example, when a marketer is promoting a new product, they can leverage the platform to tell them what types of content to send on what channels at what sequence and time to what audiences. It’s a step-by-step “recipe” that puts together all of the variables into a concise plan.
Decision Intelligence in Sales
- Faced with an abundance of options, a junior sales executive doesn’t know where to start. The leads she is given are fed into the decision intelligence platform, and she’s given a playbook combining emails and a well-timed phone call to maximize impact, based on prior performance of such an approach. These actions are integrated into her schedule, so she’s prompted precisely when to perform each function.
- A new SaaS product is being launched and targeted at existing subscribers. The sales reps need to know what latitude to apply when offering enterprise discounts. The decision intelligence platform can provide them with past performance analytics on similar campaigns for the same demographic, allowing them to set a start price and discretionary discount range with the best chance of success.
Decision Intelligence You Can Trust
RevOptics offers a decision intelligence platform that integrates seamlessly with your tech stack and pulls from multiple data sources to deliver all the insight your sales and marketing teams can handle. For more on how RevOptics can deliver your sales and marketing teams the insights they need, check out our Decision Intelligence Platform here.