We are in the era of digital disruption and it’s not just about companies like Uber and Airbnb. Organizations in every industry, because of the ridiculously fast pace of technology innovation, are dealing with disruption. They must come up with digital transformation strategies that focus on utilizing new technologies and business models to more effectively engage with customers at every touchpoint.

Furthermore, there is clear evidence that companies that embrace digital transformation and offer a superior customer experiences are outperforming their competition in terms of attaining and retaining customers.

Recently, we had the opportunity to sit down with a number of our software partners to get their perspective on how they are reacting to and taking advantage of this era of disruption. In the first of our disruption series, SugarCRM’s Martin Schneider talks with Peter Fogelsanger, the vice president of partner enablement at Thunderhead. The two discussed how Thunderhead’s One Engagement Hub is driving digital transformation by helping customers visualize a real time view of their customer journey.

 

Want to hear more partners talk about disruption? Head over to the Sugar Community to view all the disruption series videos.

 

(Editor’s Note: The following post originally appeared on IBM’s Built With Watson Blog).

In our world of high expectations and ever expanding data on individuals and brands, mastering this data and transforming it into valuable insights to inspire our human connections has become essential for brands.

Take a minute and think about this: How do your customers perceive your brand? Is your brand “shy” online and only speaks when spoken to? Or is your brand overly enthusiastic and always waving its hands in your customers’ inboxes and social feeds? Is your brand a captivating conversationalist that encourages interaction or one that’s a little socially awkward or a little too forced? Are you the tiresome talker that is always extolling your own virtues or one that expresses genuine interest in your customers and what they actually care about? Does your brand need a little coaching in the “delighting customers” department?

Real-time insights can drive meaningful conversations

Although we all seek to be that fascinating brand as we engage with customers, such mastery requires the ability to identify and collect all available and relevant intelligence and distill it down into meaningful insights that can define meaningful conversations.

Meaningful insights that are actually actionable can be attained by a variety of methods. Many data-savvy brands employ big data and predictive analytics to help identify the next-best action based on customer segments and transactional patterns, which only represents about 20% of known information about customers for most brands. Some leading brands take it a step further and use machine learning along with Artificial Intelligence (AI) technology like IBM Watson’s APIs to collect, connect and make sense of the other 80% of the unstructured data such as tweets, Facebook posts, emails, call center audio recordings and other observable customer behaviors, likes and preferences and combine it with their transactional customer data. This approach provides visibility into richer, more comprehensive behavior patterns by customer segment that offers the potential to make your exchanges more interesting, personalized, and if you are really good, even memorable.

Moving from data to insights with AI

If you are truly looking to break away from the herd and into the lead, your CRM and automated marketing platform will need to include AI and cognitive APIs. With AI, the dream can move beyond customer segments and reach down to the individual level by providing the power and speed to make sense of the enormous amount of data out there and surface true insights allowing for individual action, at scale. As the hot new brand coach, AI can lead the way to enhance the human-to-human connection for your brand by understanding the experiences your customers want.

To make your brand truly delight and engage customers, you’ll need to do the following:

  • Stop putting energy into old email marketing practices that don’t deliver and focus only on including the high-value information that is worthy of your customer’s time and attention. If frequent messaging or notifications are important to your core value proposition, only do so based upon explicit customer preference.
  • Be very selective in the type of metrics you choose to run your business. Diligently focus on the ones that are truly your key performance indicators versus trying to distill insight from low value information.
  • Invest in a CRM system with embedded AI that tells you something you don’t already know about your customers by combining behavioral data from both your backend systems and available external and publicly available data sources.
  • Get an automated marketing platform that is synchronized with your CRM system and employs AI so that it allows you to better plan interaction flows, communicate consistently across channels and recommend next best action.

To learn more about how you can truly supercharge your brand’s marketing and customer engagement efforts, download the IBM and SugarCRM white paper: “Becoming a Brilliant Brand Conversationalist.”

robocopRemember when SaaS CRM companies needed to build their own multi-tenant architectures to bring their CRM to market? And how they needed to maintain expensive and unwieldy architectures that took focus away from actual product development? And how the cost and complexity of said proprietary architectures was passed along to the customer to maintain revenue goals?

Oh wait. That’s still going on with companies like Salesforce.

But, even Salesforce has finally admitted that CRM vendors should not also be cloud infrastructure providers anymore. The company’s recent partnership announcement with Amazon tells us all we need to know. Salesforce needs to focus on innovation, since its core product is old and the cost of maintaining the underlying delivery and development infrastructure itself is proving costly.

So, why is Salesforce potentially repeating past mistakes by trying to create a proprietary AI product for CRM?

Let me explain. What I see brewing with Salesforce’s Einstein concept is a hodge-podge of Wave analytics, generic machine learning (pieced together by several small pocket acquisitions), SalesforceIQ, and elements of Data.com – all components of Salesforce’s portfolio. In short, Salesforce is building yet another proprietary stack in AI.

By “owning” the entire stack, one could argue the profits (as noted, something perennially eluding Salesforce) can be much higher. But at what cost? By instead focusing on integrating industry standards and expert-AI platforms into its tools – a CRM provider can have more flexibility and be able to keep up with the rapid pace of change.

Today, companies like IBM with Watson, and Amazon with its AI platforms are opening these up to software manufacturers as a service. These companies have both the deep pockets and expertise to offer broad and even focused AI-tools for CRM usage scenarios – without CRM vendors having to do much if any heavy lifting.

Here at SugarCRM, we are taking a “best of breed” approach for a number of reasons. One, it will speed our time to market to leverage pre-built, highly scalable and proven AI toolsets and platforms. And, of course, the cost to bring AI-powered CRM offerings to our prospects and customers will be lower, which we can pass on to the user and remain a value-driver for our partners and customers.

And again, by leveraging larger platforms and standards, we will be more nimble than those building hulking masses of analytics engines, giant data warehouses, etc. We will be able to quickly hone our offerings to adhere to market demands, without having to re-architect massive purpose-driven AI stacks.

In short, it is becoming clear to me that AI is an arms race – and categories like CRM should not be trying to reinvent the wheel. Just as with cloud delivery – when you integrate and build upon expert, proven strategies – you can cut costs, speed time to market, and focus on building exceptional customer experiences.

 

(Editor’s Note: the following is a guest blog post from Sarah Friedlander Garcia, the director of marketing at W-Systems. It originally appeared on the W-Systems blog. For more blog articles from W-Systems visit the company’s SugarCRM Blog.).

Silo mentality has become a major problem in organizations across the globe. Today, the lines between sales and marketing teams have become blurred. Marketing teams are often tasked with converting new leads from social media interactions, emails and website visits into customers –  traditionally a sales role. Meanwhile, many sales reps are using these same vehicles to gain insight into a customer’s buying behavior – traditionally the marketer’s job. Organizations must do a better job at clearly defining the roles of sales and marketing, where marketing generates leads and sales closes them.

Software as a Barrier

Technology now serves as another reason for silos between sales and marketing teams. If sales reps are using a CRM platform to manage their customer relationships and marketing is using a marketing automation platform to manage their leads and these two systems aren’t sharing information, it’s a recipe for disaster. A disconnect between sales and marketing can lead to lost opportunities and lost revenue. Then sales and marketing teams are left pointing the finger at each other.

Better Together

Successful organizations need to utilize both CRM and marketing automation systems. However, these two systems must have the ability to share data. By connecting these two systems together, organizations can fully realize the value in each.  Marketing automation is worthless if salespeople aren’t closing deals from the leads provided.  Likewise, CRM is a useless prospecting tool if it is not being fed quality leads from marketing.

The Dynamic Duo

In many cases, you’ll find CRM and marketing automation platforms on the market that offer integration on a very basic level. Unfortunately, basic integration yields basic results. And world class sales organizations need to be much more than basic to compete in the current hyper-competitive landscape.

Marketing automation solution Act-On integrates deeply and seamlessly with Sugar CRM, providing a complete, closed-loop system for multi-channel lead generation, management, and revenue contribution. Act-On features a native, out-of-the-box integration with Sugar, allowing sales and marketing teams to set up automatic bi-directional synchronization between the two platforms.

Synergy at Work

This deep integration allows marketing to deliver highly qualified leads to the sales team, while allowing sales to access those leads and activity histories, personalizing their sales pitch to the individual, in real-time. This is powerful stuff. A sales rep that knows a prospect’s preferences, behaviors and activity history before the call, changes a cold call into a warm call, makes the call more satisfying for the prospect and has a better shot at making the sale.

Studies show that when both sales and marketing teams are in sync, companies become 67% better at closing deals. Therefore, an integration of the technologies used between sales and marketing teams are imperative to breaking down the information silos that exist between them, opening the door to realizing the ultimate goal of both teams – increased sales and revenue.

Artificial Intelligence is all the rage right now, and it seems companies in every industry are talking about how the magic of AI will change everything. And, when I say every industry, I mean every industry.

Here’s the thing, the potential of AI has been something that data scientists have been touting since the 1970s. This time though, it does feel different. It feels like we are on the verge of AI changing the world forever.

I recently caught up with SugarCRM’s chief product officer Rich Green, a man who has lived through many technology crazes, to get his thoughts on what is different this time around.

Q: What’s Different About AI Movement This Time Around?

Rich: The biggest difference this time: the people who are leading innovation in AI are the same people who are using AI every day. Instead of a university of governmental lab working on AI, you have companies like Facebook and Google who have the deepest pockets, largest data sets and best data scientists. They are the ones working to improve AI and they have the easiest path to integrate what they are working on into today’s world.

There are a couple other big differences. For one, AI related techniques like machine learning get better with more data to interpret. Nowadays, the pool of data is so large that you can expand AI beyond narrow uses cases and do more interesting things, and the statistical accuracy if far greater due to big data. Secondly, the computing power required to do AI has caught up. We have cracked the “AI speed barrier” with hardware and algorithms. AI used to be clumsy and obtrusive, it’s now transparent and can be transparent to people, not having to internalize that many of their connected experiences is powered by AI technology.

Q: I think the industry is still debating what’s really AI and what isn’t. Where do technologies like machine learning, deep learning, neural nets fit into the AI category?

Rich: As you note, AI is a category, not a specific technology. Machine learning, deep learning and neural networks and many other technologies are all part of the AI category. The industry likes to debate what is AI and what isn’t. I argue the sum of technologies fundamentally required to create an evolving intelligent digital assistant, self-learning, self-driving cars and chatbots that incrementally improve their accuracy all fall into the AI category.  Tools like Google Translate  now use machine learning AI to rapidly improve and provide remarkably accurate translations. In fact in that particular case, the system did something particularly remarkable.

Q: In the past, many people working at the edge of AI technologies have grown disillusioned, and this has stalled progress. Do you think this will happen again?

Rich: That’s highly unlikely. Many of the world’s best AI researchers are no longer confined to pure research in academia. Instead they are spending some or all of their time with Facebook, Google, Amazon and others and are able to leverage the breadth of resources, data and access to accelerate their work. And while that is happening, they can test and validate their work using the largest data and computing engines in the world. With such access and the freedom to experiment and deliver, the pace of innovation is accelerating at an unprecedented pace.

Until recently, there used to be a significant delay in moving research to advanced development and ultimately delivering innovation to a wide range of users. That delay is now compressed because of the tight cycle between research and availability.

Q: Are we currently at peak hype for AI?

Rich: ‘Hype’ is an interesting term. It typically implies that the commentary and the reality are disconnected. Today there is a great deal of discussion and visibility but unlike the past, most of it is either true or will be true quite sooner than most people are able or willing to believe. But we are just scratching the surface of actual capabilities and utility of AI technology. Unlike the 70s and 80s, we are on a very steep slope of growth. There is no logical impediment to this hype cycle.  

(Editor’s note: Thanks to Chris Bucholtz, who wrote the original version of this post for CRM Outsiders in July 2012).

When our sales team is in the early stages with potential customers, one of the first lengthy discussions is about who should be in the room and part of the CRM selection team. These are the folks who mull over what’s important and what’s not in the CRM they ultimately select.

Most companies pull in the big shots – the vice president of sales, the head of IT, maybe the chief marketing officer, whoever’s in charge of customer service, etc. They huddle up (and, perhaps, bring in their seconds-in-command) and out of this esteemed group comes a choice.

That sounds reasonable, right? Well, perhaps. However, the biggest hurdle to new CRM deployment is adoption – and that doesn’t mean the VP-types using the application. It means the people on the front lines in sales, marketing and service embracing the application and using it to its full potential. When that happens, the efficiency improves and people become better at their jobs. Oh, and the VP-types get complete their coveted reports full of comprehensive and complete data.

But in order for that to happen, you need an application that the front-line folks will use. Sadly, the VP-types don’t always guess right; they look at applications through their own set of agendas and needs, and the choices they make sometime end up alienating the front-liners, thus setting the stage for adoption challenges.

So, back to the CRM selection team – the best way to prevent a misalignment between the front-line users and the executives is to make sure front-line users are included on the CRM selection team. Furthermore, it shouldn’t be people selected at random, but people with some experience, knowledge of the processes that CRM is intended to help improve, and a decent understanding of their fellow employees’ behavior.

Not only does this get past the traditional issue of the application being selected by people who may not use it every day, but because it also creates a set of advocates who can hype the virtues of the new CRM for their peers. The perception becomes not that the application is something picked by management and dropped on the front-liners, but something that their peers helped select to make their lives easier. It helps with both the logistical and perception issues that can hinder CRM adoption.

This all sounds pretty reasonable right? I can almost feel your heads nodding. So, how often does this happen? Sadly, not very often. No matter how logical it seems, there is often pushback: choosing a CRM is too important to be left to the people who most frequently use it.

This is upsetting for those of us that live and breathe CRM. But, it also gives smart companies a chance to gain an edge. If you can be one of the few mavericks to reject the status quo type of thinking, you’re much more likely to have a smoother implementation and a quicker rate of adoption – which will mean better ROI from your CRM, happier employees, and a better and differentiated experience for your customers.

And that’s what you want, right?

If you’ve included front-line users on your CRM selection team, drop me a comment below and let me know how it went.

NLP (Natural Language Processing) is a big topic and a quick google search reveals several definitions floating around the internet. Here’s one more from SugarCRM’s perspective: NLP analyzes communications in emails, LinkedIn, Sugar and other sources between customer facing professionals and their contacts to keep their relationships on track, helping the former provide a better customer experience to the latter.

Definitions are fine, but let’s take a look at three ways that NLP will enhance the customer experience

  1.     Determine what customers are asking for when they send an email

This is the most basic use of NLP. NLP gives employees a head start on what a customer is requesting via email. Here’s an example, a SugarCRM customer in the financial services space is using our CRM for their customer service department. Many of the requests their support staff receives are common: transfer money from one account to another, replace my debit card, change my address, etc. NLP technology can scan email before the user even opens the message and get the process started. 

  1.     Communicate Urgency

Scanning for keywords and phrases to determine what the customer is asking for is NLP 101. The next step is to examine an email and determine urgency. Building on the example above, a request for “lost debit card” while “on vacation” is something that is likely urgent. A change of address request, while important, doesn’t reach that level of urgency. NLP can help push the urgent requests to the top of the of the customer service agent’s queue so they know what task to tackle next.

  1.     Determine customer satisfaction.

How many times have you been asked to take a “brief survey” at the end of a support call? Consumers are drowning in a blizzard of customer surveys and smart organizations are starting to realize many people find them impersonal and annoying.  

Enter NLP, which has the capability to examine email interaction between the employee and the customer and determine how happy, or how unhappy the customer is with his or her experience. Organizations can then step in and reach out to the unhappy customers much faster to remedy the situation. 

These are just three basic ways leveraging NLP technology with your CRM can increase customer satisfaction, streamline processes and reduce costs. The great news is that SugarCRM is moving quickly to add more NLP-based features and tools to its offerings – like our recent partnership with TrustSphere.