As a technology vendor or solution provider, it’s easy to say that you want to have the relationship with your client at the highest level internally that you can get – like the CEO, ideally. A relationship with the CEO means if she says so, then it’s gonna happen. Of course, there are some solutions where it would be ridiculous or ludicrous for the client CEO to be the owner of the vendor relationship. Does the CEO need to own the relationship with a retailer’s email solution provider? Probably not.

Conversely, if you provide solutions that are broad and strategic, you probably need that CEO relationship. It’s the only level where a decision can be made without needing to have a room full of people come to some kind of consensus. For example, if you’re providing IT outsourcing for the whole department. That’s an executive leadership level question. Or an ERP solution. It’s a good rule of thumb that as a solution provider, you need a relationship at the level that is proportional to the value you’re delivering to the company.

But what happens if your value proposition changes? If you start out as a specialized provider and grow into something much more strategic? How do you expand the relationship with your client so that you can reach that all-important CEO level, and once you get there, how do you make sure that you can maintain that relationship – that you can continue to deliver value not just at the company level, but at the executive level?

I think this is going to be the big challenge for SAS going forward. I just spent some intensive time with both SAS management and the retail and products teams specifically, at SAS’s analyst day in Steamboat, CO. I’ve been attending this event since 2007, amazingly enough. Over that time, through my admittedly retail-specific lens, I’ve seen SAS evolve from a company assimilating MarketMax, to one rationalizing industry-specific solutions against a broader set of analytics tools, to an analytics platform that has both general solutions as well as industry-specific ones.

Every year I see the demos and re-familiarize myself with the company’s full product set. As someone covering retail, it’s easy to forget that SAS provides some really impressive solutions around insurance fraud, for example. Over the years, and I think I’ve been pretty open about this, I’ve felt a little bit of disconnect when it comes to the retail-specific solutions of merchandise planning, price optimization, and size optimization, and the rest of the suite. I left Steamboat this year thinking that I finally have my arms wrapped around how all this works together.

On top of SAS’s analytics platform sits a bunch of solutions, but the ones that I care about most for retail are: Customer Intelligence, Fraud & Security, Network Analysis, and Visual Analytics. That’s not forgetting about merch planning, price, and size optimization, which also sit on that platform.

SAS has some really cool things coming out around security and fraud, which historically have been targeted to financial services, but increasingly apply to retail – stay tuned for more on that. We got a preview only. But when SAS is ready to talk about what they’re doing, pay attention. It’ll be good.

And Customer Intelligence has always been highly embraced by consumer-facing industries. The customers at the event spoke of predictive net promoter scores, and mining customer behavior and natural language feedback to improve everything from customer service to packaging. And that’s without even getting into executing on those insights, or even better, connecting digital insights to in-store behavior.

The main use-case for Network Analysis is insurance fraud – detecting relationships between people and entities and claims to identify rings of people perpetrating fraud. But every time I see it, I think of the vast amount of relationship data that retailers have – ship-to addresses, Facebook relationships, etc. I feel like it wouldn’t take much for that Network Analysis to be extended to understanding relationships from a marketing perspective. Not just who has the most reach or greatest influence, but who can actually influence purchase.

And then when you bring in the retail-specific apps, things get even more interesting. Merchandising and Customer Intelligence is an area that I have long thought has huge opportunity for SAS. At RSR, we see retailers struggling with how to make their merchandise planning processes more customer-centric, and here is a solution provider who has both capabilities not only under one roof, but operating on the same platform. Hmmm.

And then throw in social media analytics, and some of the feedback loops that their customers are talking about. Sure, it’s great to use social media to understand customer service breakdowns. But it’s even better if someone could find a way to unlock the predictive power of the purchase intent that is often expressed on social media – if that could be harnessed to understand its impact on demand, now we’re talking about a very real, very defined ROI for social media investments. Who could bring that together? Hmmm.

Even more interesting would be understanding if you can use customer network analysis to assist in identifying whether a network effect could be used to predict demand, or at least to predict an impact on demand. This would almost be like being able to identify a tipping point (who knew that black skinny jeans would take off?) as soon as the point tipped. Who could bring that together? Hmmm.

So why is that opportunities like these might become a challenge for SAS? Well, I think in retail SAS has had something of bi-polar image: the white lab coat kind of people who interact with the deep dark marketing analytics folks, and the merchandising/pricing/size optimization people. One group is very analytics focused and out of the core SAS platform. The other is business process focused, with most of its relationships in Merchandising.

But one thing that I don’t hear a lot of people talk about in the industry is that omni-channel transformation is fundamentally a transformation driven by data. Yeah, you hear all about “big data ” and all that, but it’s almost isolated from omni-channel as a trend. But one thing omni-channel has done is provide access to data about how consumers shop and how the business is run that retailers never had access to before. The whole digital life of consumers never really existed until this century. All that research and pre-shopping activity that happens online today used to happen in the store. And it was only ever really captured anecdotally, never in a systematic way that enabled any kind of analysis or real insights – not like we can get from online interactions today.

The retailers who pull all of this new information together and find a way to drive value out of it are the ones that stand poised to make the most out of the future of retailing. I mean, Amazon’s valuation isn’t based on their ability to sell products. And certainly not based on their efficiency in shipping them. It’s based on their ability to gather and use data about their customers. Google too – you think if they billed themselves as an advertising company they’d have the valuation they do? Heck no. Why do you think so many people protested about Google’s acquisition of Nest? Because everyone knows already that Google collects way more information about you than you’d really like to consciously think about. And they are spending an awful lot of time either figuring out how to get more, or figuring out how to use what they’ve got to make money.

It’s about data. And insights. And being able to make connections across your business and use the understanding from those connections to make strategy. To create differentiation. That’s a CEO-type message. It’s a holistic platform message: SAS is passionate about turning data into actionable insights. They do that through a collection of software and services, and they happen to have applied it to one of the most data-rich and disrupted industries out there, which is retail. That’s a powerful message.

But that’s not quite the message that SAS is delivering today. And in order to hold a CEO’s attention span, they’ll need to be a lot more thought leader-y about how to unlock value from data, and a lot less data science-y. They’ll need a lot more of a platform message, and a lot less of merch-price-size hanging off the platform without a lot of explanation for how it really is a part of the platform, and not something tacked on.

I think they’ll get there. And I think when they do, they have a chance of changing how the industry talks about analytics. And about how to create differentiation in retail. Like I said, a powerful message.