Prescriptive Analytics – Let Me See You Work

Prescriptive Analytics – Let Me See You Work, Work, Work

Prescriptive Analytics – Let Me See You Work, Work, Work

After a deep dive into the inner workings of one class of prescriptive analytics—recommender system (personalization engines), it’s time to step back and explore how we can leverage prescriptive analytics in general. Today, I am going to outline 3 relevant use cases:

These are very distinctive use cases, where the objectives being optimized are drastically different. I hope these examples will not only demonstrate the power and versatility of prescriptive analytics, but also give you a better understanding of how they work. (If they don’t please feel free to let me know!)

I’ve discussed before that the simplest example of prescriptive analytics is a GPS, which operates in the geospatial domain. In general, prescriptive analytics are not limited to geospatial optimization. We can optimize processes and other parts of business operations. One of the most common use cases of prescriptive analytics is business optimization. Since the underlying computation of prescriptive analytics is already an optimization of some objective, this application is very natural. In this case, the objective we optimize is typically the efficiency or throughput of the process.

Whether you are optimizing a business process in marketing, sales, or customer service, you must tell the prescriptive analytics system what you are trying to achieve. This is like telling the GPS where you are going. For example, increase conversion by 10%, increase sales by 20%, or increase your net promoter score (NPS) by 5 points. These are the goals, or “destinations” you are trying to reach in a non-geospatial domain.

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Subsequently, the prescriptive analytics system would prescribe a sequence of actions that lead to the corresponding business outcomes you want (i.e. increase conversion by 10%, sales by 20%, or NPS by 5 points). For example, to achieve 10% conversion lift, the system may prescribe reducing the frequency of your email marketing by 35%; simultaneously increase your real-time social media engagement by 30%; and when your real-time engagement reaches 15%, start directing people to your customer community for peer-to-peer engagement and recommendation. These are like the turns that your GPS system advises you during the journey, except these directions are not in the geospatial domain.

Now you know what prescriptive analytics can do for your business, let’s dive deeper on how it prescribes actions. The key lies in the objective that’s being optimized. Let’s examine a couple of examples from social media.

These days, social media is not new to business, but many enterprises still struggle to figure out how best to leverage it. Because there are so many different things you can do on social media, it’s hard to determine where to best allocate your limited resources (e.g. time, money, energy, etc.). Should you create more YouTube videos or should you use Snapchat? Should you publish more blogs, or participate more in the Q&A section of your community? The social media landscape is complex with thousands of social channels. Even within a single social channels, there are probably a handful of actions you can take. Take Twitter for example. It’s probably one of the simplest social channels out there, but you can already engage in many different ways: tweet a message, reply to one, retweet it, favorite it, follow someone, or simply read the tweets coming out of the firehose. This gives rise to many different social metrics that quantify how you engaged on social media.

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Prescriptive analytics can help you focus on what you should do to achieve the biggest impact, but you must tell it what kind of impact you are looking for. Whether it’s increasing marketing conversion, sales, or customer satisfaction (CSAT), you should be able to measure the impact you want to drive. This is typically a key performance indicator (KPI) for your business.

 



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