photo of a man working on intelligence systems

Solus Intelligence Systems: Enhancing Performance & Efficiency

2022 has been an interesting time for folks in tech– and as you well know we’ve pivoted so much to being a tech-first organization that suddenly everything happening in tech impacts us too! We shifted to being product-first in 2020, and the roller coaster ride that followed is worthy of a small book – or lengthy blog post at the very least. But that’s for another day. Today I’d like to touch upon one of the three main pillars of Solus AI. For context, the three central systems of SOLUS that work together to create magic are: Recommendations Systems | Smart Campaigns | Intelligence Systems

Intelligence Systems in Solus

Part of our entire pivot to being product-first meant that we had to go back to our “greatest hits” of analytics work done over the last decade and see if we could make them available to clients using Solus. But of course, better than before – configurable, always on, and far richer. One decision we did take however is to not create a dashboarding platform – we’re not trying to build a Tableau/ PowerBI, but we’re bringing in our experience of how one should look at CRM and campaign metrics, and making the best of that experience available.

I’m happy to share that the Solus Intelligence System module has matured beautifully over the last year. This is a quick recap of where we are, and where we’re headed with it.

You might like to read how the power of customer Insights helps unlock hidden opportunities for your business.

Customer Intelligence Systems Report

We’ve ramped up the Intelligence systems reports to over everything a CRM manager (or someone dealing with Retention or targeted campaigns) might need. We’re constantly adding to these reports, so while these are currently a set that would work for pretty much any industry, we’re next coming up with industry-specific reports too.

Campaign Performance Reports

In addition, the ability to track campaign performance has been greatly enhanced as well. We’ve focused on Incrementality measurement – which we all know is hard, but also the truest measure of impact, and what we’ve added is a whole lot of reporting that comments on what’s working, what’s the yield it’s generating, what consistently works etc.

A few things we’ve added to these reports that are small, but powerful:

  • The ability to filter out triggers where the Control Group is too small
  • The ability to switch between Trigger X Day and Trigger X Month level of granularity for Lift measurement
  • The ability to make response attribution Time relative rather than Day relative

 There’s so much more, and we’re truly helping clients see beyond clicks and conversions, the true impact of their customer-centric efforts.

Roadmap Stuff: Campaign Diagnostics (and soon enough – What Ifs) 

We aren’t stopping here, of course. A big ask has been – can we help diagnose what campaigns work/ don’t work better? Can we understand what aspect of the campaign works? So we’re now coming up with a campaign diagnostic that does exactly that. What campaign attribute works? The segment being targeted? The use of a personalization engine? The timing? The presence of an offer? The use of a Recommendation? And so much more.

The obvious next step from here is adding a What If, going Prescriptive – recommending campaign types that give you lift and incremental, as well as campaigns that give you coverage and absolute numbers. Answering the Q of – “What If we run these types of campaigns in the coming month”. Getting to goal-seeks “IF I want to attain X, what should I do?” Watch this space!

Looking Ahead

Building Solus has been an immense endeavour. No part of this is easy – CRM is complex, it’s quite literally a space in which everything that can go wrong, will. Personalization and scale are notoriously hard. If you think about it, however, we are driven by a not-complex goal to help brands derive the most value from customer intelligence systems. This translates into – uplifting how brands nudge customer behaviour, whether the context is brand initiated (you nudge them by sending the customer a message), or customer-initiated (the customer comes to your app/ website and we need to decide what to show and how to engage them). We’ve had to break and build like crazy this last year, and the coming year will no doubt be the same. 

In conclusion, if you’re looking to unlock the true potential of your business and drive long-term success, an intelligent campaign & customer insights solution is the key. With our powerful AI-driven platform, you can gain invaluable insights into your customers’ behaviors, preferences, and purchasing patterns. By harnessing these insights, you can create highly targeted and personalized campaigns that will not only increase repeat purchases but also foster customer loyalty.

A magnet attracting target customers

Solus Updates The 4th Pillar, Predictive Scores For Targeting Customers

We would like to share an exciting update with you on Solus about Predictive Scores For Targeting Customers. But first, some context:

Systems of Intelligence

We built Solus; a personalization engine to be a System of Intelligence. This concept has been around for a few years now. In our context, they sit between Systems of Record (Data sources) and Systems of Engagement (marketing systems) and do automated decision-making and optimization. Or at least assist the decision-making and optimization. Given our focus on customer value, we knew the decision-making had to revolve around the following:

  • Who do I target (The List)
  • What value proposition do I target them with (The offering or offer)
  • What message/ tonality/ cadence
  • When do I target them?
  • What call-to-action or Response devices do I use?

Do a good job on these, and the customer retention and engagement world is yours. You might find Unlocking Insights from your Customer data worth a read too for more strategies.

The Fourth Pillar; Predictive Scores for Targeting Customers

In SOLUS we focused on building Recommender and Smart Campaign systems in the early couple of years. Then, more recently came the Insights system. We now have the fourth pillar in place – the Predictive Scores system for targeting customers.

 Four Pillars of Solus

Predictive Scores

Predictive Scores for targeting customers have been the bread and butter of the analytics world for years. They’re the go-to project for any data sciences team wanting to help marketers get better ROI. What we’ve done, is make this out of the box, incredibly usable, and very accurate.

 The scores themselves will focus on familiar goals:

  • Who is likely to buy in the next N days (7/15/30 days, for instance)
  • Who amongst the new customers is likely to Repeat
  • Who amongst the customer base is likely to Churn
  • Who amongst the lapsed base is likely to be won back

We won’t stop here, of course. We’re next setting our sights on that most elusive of concepts – CLTV.

The models behind these are ML models – gradient boosting/ random forest for the most part – and have been fine-tuned to work quickly, and smartly. What often happens in data science projects is that there are folks that love building models, but putting them into regular production is much harder as that needs a different set of chops altogether. We’ve solved this:

  • The predictive scores for targeting customers are available at a customer level as ready-made variables to use in campaign selections
  • Ready segments are available (Top 30% by Likely to Buy etc.)
  • The segments can be combined with other segments for targeting (High Propensity + High ABV, for instance)
  • A ready reporting interface with gain charts and model performance
  • Configurations through a UI to set the refresh and calibration cycles etc.

This here’s a sample chart for the models that will be part of the UI:

A chart showing predictive scores for targeting customers

 The Impact

  • The obvious impact is that of time usually taken to get this nature of tool kit in place – many months of work get instantly taken care of.
  • The business impact comes in sharper targeting = better conversion rates
  • The Customer impact comes in better relevance = lower dissonance and better LTV

We’re looking forward to putting our Predictive Modeling Software for targeting customers to work!

Two individuals with a graphic of bulb discussing hidden potential of Customer Insights

Unlocking Insights from your Customer data

It’s never been more important to understand your customers in a way that is useful for driving revenue for your business. All leaders need to know how to leverage customer insights and drive more revenue from returning customers, and the literature around why this is a better ROI than constantly acquiring (and losing) customers is legion. Here are a few tips on making this come to life:

An Insight into Customer Insights

While Customer insights appear to be all about understanding customers’ needs, behaviours, preferences etc, not all insights are equal. The first thing to figure out how far you’re going to get is to know the entitlement you begin with – the data you have. 

Our view is that the best stuff comes from the transaction and behavioural data, and less from profiles and demographics, for a couple of reasons:

Transactions and Behaviours are good data

These come from billing or online systems, are first-party data you own, and contain enough signals to make many of the decisions you need. If your goal is to figure out who’s going to do a Repeat transaction, there’s enough in the transactions and behaviours to go by, without waiting for Profile information.

Profile data = Infinite Procrastination

For many industries, waiting for profile data can be an infinite wait. You need to put in place systems to capture it, send out profile-update surveys, get front-line staff to ask Qs and so on. This can take a very long time to give you a half-decent fill rate in your customer database, which is time lost.  

Similar Profiles have vastly different behaviours

If you’re looking at predicting which of your churn base is likely to be won back, chances are there’s little commonality from a Profile perspective that will help. Gender/ Location/ Income etc don’t help much when it comes to predicting behaviour. They do help a LOT when it comes to getting the right tonality, but from a sheer utility perspective – our approach is to tap into transaction data first, and fast, before getting to profile information.

Customer Insights (that are worthwhile)

Of the many customer insights you might seek, we’ve found a few to be more immediately useful to drive business goals:

Lifecycle Behaviour

The simplest, the most insightful, and yet oft-overlooked. Lifecycle insights are simple metrics that tell you how healthy the customer base is. These help set goals and can drive the entire CRM effort. Sample metrics include:

Repeat behaviour: How many repeats, and within what time frame? What is the contribution of Repeat revenue in a month as against New revenue? 

Retention Metrics: A variant of Repeat, this typically looks at how many customers that transact in a year are retained in the subsequent year. 

Churn and Winback Metrics: How many customers are lost, after how long do we call them “churned”, and how many of them are won back? 

Stickiness and Stars

Insights into what makes for a loyal or “sticky” customer. What they buy, how often, how quickly etc. Loyal and Star customer profiling provide a wealth of insight into the ideal customer behaviour you’re chasing.

Product Adoption

Combining product adoption with lifecycle thinking leads to some great insights. Instead of just looking at what is the product mix being bought, one looks at what’s the mix at different stages of the lifecycle.

What’s the entry point, and also what was the entry point for those who went on to become Star customers? Which product seems to lend itself the most to repeat? How much is the category adoption amongst customers and what are the category associations? And finally, what seems to be most associated with customer churn?

Location/ Temporal

These often go hand in hand – insight into what makes a Location different, as well as what is the buying pattern over time bands – days of week/ month part/ season etc.

Here again, combing Location/ Time data with the Lifecycle often gives the best insight. Knowing that there is a sub-segment among your Stars that are weekday buyers is useful to craft targeted campaigns just for them.

Campaign and Offer Responsiveness

Finally – a great piece of insight to delve into is to know what nature of nudge works to get customers to buy. Does it work better to send personalized messages? Do recommendations work? Does day and time matter? What’s the right cool-off between messages? What tonality resonates?

Putting this to use

Do better Targeted Campaigns

Better, more targeted, hyper-personalized campaigns that get better conversions and Lift. The starting point to these is knowing your customer better.

Do better Mass Campaigns

Mass Campaigns can and should be smart campaigns. Yes, you may talk to the entire base but the offer and tonality may vary by segment. Timing can be picked, the offer can be tweaked.

Set better Goals

It takes insight to set good CRM goals – what Repeat/ Retention/ Churn Prevention and Winback goals you chase come from the customer insight you have.

Improve your ROAS

The ultimate goal is ROAS – get more revenue, at a lower cost. Which means better targeting without missing opportunities.

Align the Org. for Loyalty

This doesn’t mean a Loyalty Program. This means the always-on hunger for customer insight and how to put it to use to retain customers, better. Stay customer-obsessed, by being data-driven.

Why SOLUS AI?

We’re a System of Intelligence providing a personalization & decision engine, built for Customer obsessed businesses. While at one end we operationalize Recommenders, Predictive Scores and Smart Campaigns, an equally large part of our value proposition is getting businesses closer to their customer data by giving them all the customer insight they need, on tap. 

These tools include:

  • Repeat customer base and revenue tracking. 
  • Bounce curve or Interpurchase cycle tracking.
  • Repeat Cohorts.
  • Glue number and Glue cohorts. (how sticky is the customer base)
  • Multiple Segmentation schemes with segment profiling.
  • Customer frequency distributions.
  • Segment movements over month/ quarter/ year.

SOLUS AI’s Campaign Insights revolve around Incrementality measurement and encompass:

  • Outreaches and channel split.
  • Incremental Revenue, Lift, TG vs. CG metrics.
  • CRM KPIs tracking such as Repeat, Retention, Winback etc.
  • Any vs. Hard Response. (bought the specific product)
  • Conversion Analysis – what was bought in the conversions. 
  • Attribution views – Last Touch vs. MTA
  • Yield reports that specify the ROI from campaigns.

In conclusion, if you’re looking to enhance your user experience and maximize the potential of your business, look no further than our machine learning-based recommendation system. With cutting-edge technology and expertise in artificial intelligence, we have revolutionized the way businesses connect with their customers. Contact us for intelligent campaign & customer insights.