What is Sales Enablement? - Part 2: Analytics Enablement

In this post I laid out IDC’s original definition of sales enablement (i.e., “putting the right information into the hands of the right sales professional at the right time, in the right place, and in the right format to move a specific sales opportunity forward.”) and discussed some reasons for why we wanted to expand on it.

As part of that, I outlined three core sales enablement activities and discussed the first of these at length:

  1. Education enablement
  2. Analytics enablement
  3. Asset enablement

In this post, we’ll turn out attention to analytics enablement.

Analytics Enablement

Analytics enablement describes the software workbench that is jointly used by marketing and sales to closely monitor the buyer’s journey, with the objective of assessing their areas of interest, purchase intent, and urgency so that a smooth and timely introduction from marketing to sales can be affected when the time is right. When this introduction is made, analytics enablement also provides salespeople with as much information about the buyer as possible (e.g., footprints of interest left by the buyer during their online exploration), so that salespeople can quickly and efficiently pick up the interpersonal dialog while incorporating the knowledge already gained during the digital dialog.

It’s fairly obvious from the above description that I’m describing an idealized version of how things work in large organizations where the customer-creation process is divided into at least two major parts: the first covered by marketing, the latter covered by sales. I’ve also used a couple of terms that require definition: digital dialog and interpersonal dialog. The digital dialog is that part of the customer-creation process, managed by marketing, that engages the buyer through digital means, including advertising, Web sites, and email. The interpersonal dialog is that which ensues after sales engagement takes place, and is managed by the sales organization.

Thanks to the advent of marketing automation solutions, interaction during the early stages of buyer engagement can be very sophisticated, tracking buyer interest based on which emails and Web pages the buyer viewed and providing progressively more relevant information as a profile of buyer interest is developed. Thanks to this modern approach to lead nurturing, prospects can be scored so that only buyers most likely to be genuinely ready for sales engagement are passed along as leads.

In reality, this is rarely a perfect process, with the quality of leads being handed to sales a source of constant debate. That said, this digital dialog has had a dramatic impact on the customer-creation process, enabling a great deal of self-education to take place by buyers. Buyers like this ability and take advantage of it to better understand their options prior to engaging with sales.

This delayed engagement with sales means that today’s sellers have a smaller window of opportunity in which to influence the buyer’s journey as they pick up the interpersonal dialog that is theirs to manage. It also means today’s buyers are a whole lot smarter than they used to be and are looking for a different type of interaction. Gone are the days where buyers are happy with a long, drawn out sales process in which sellers can get to know the buyer as they impart hard-to-find product knowledge. Today, buyers get this information online and often understand their options better than many sales reps, especially when we include an understanding of the competition. This lost opportunity to gain buyer knowledge is why the Market and Buyer Education I discussed in my last post is so important. It’s also where analytics engagement can really help.

By providing information about specific buyers and selling opportunities, analytics enablement can send important signals to other parts of a selling organization’s enablement framework. For example, data indicating a particular prospect is a chief security officer at a healthcare company can trigger the delivery of training content tailored to that industry and persona-specific conversation guidance. Likewise, this same prospect might trigger a suggestion that the sales rep share a recent blog post or other thought leadership piece that is of particular relevance to that persona and industry.

This need to provide training that supports interaction with a particular buyer profile associated with a specific opportunity is a key driver of the trend toward microlearning. As described by Brian Leach in a blog post on the topic, microlearning is “the practice of delivering training in smaller, more focused chunks that learners can easily digest without committing large amounts of time to training.” Given the greater diversity of today’s buyers, this kind of “just in time” sales training, empowered by modern analytics enablement, can do a much better job of delivering sales enablement content exactly where’s it’s needed, just when it’s needed.

In addition to signaling when and where to deliver what sales enablement content, analytics enablement can also greatly enrich the lead handoff process. Just as a buyer’s interest profile developed by marketing automation systems can inform the lead nurturing process, it can also be used to educate salespeople about the leads they are being handed. Sadly, however, this information is rarely transmitted along with the lead. When it is, it usually takes the form of a raw data dump: pages visited, filed downloaded, etc. To understand the buyer’s areas of interest, the rep must go and view those pages and files and infer why the prospect chose to view them.

A much more valuable and efficient use of this data would be to pass along insights about what a prospect’s behavior during the digital dialog tells us about their interest and how and where the rep should pick up the conversation when they are engaged. This approach provides a much smoother transition between the digital and interpersonal dialogs and a better experience for the buyer. I can’t emphasize this last point enough—failure to provide reps with as much insight-level information about the buyer as possible during lead handoff forces the buyer to hit the rewind button and educate the sales rep about their areas of interest. This is a waste of everybody’s time and a big driver of buyer frustration.

It’s worth noting here that lead generation campaigns that make use of online tools to trade valuable information (e.g., technical maturity or business value assessments) for detailed prospect information (some of which is gathered as part of the assessment; some of which is requested in exchange for downloading the assessment report) can be another source of invaluable data. By embedding the collection of valuable prospect data within an experience the buyer finds worthwhile, marketers can not only learn a great deal about their target audience but also collect information of high value to downstream selling efforts. It’s well known that asking for prospect information lowers the likelihood that documents will be downloaded, but tools that provide real perceived value — benchmarking against peers is an excellent example — can often overcome this resistance and get prospective buyers to share their info.

As I’ve emphasized above, the more prospect information that can be gathered prior to sales engagement, the better enablement activities can be activated to produce highly relevant sales conversations

Sales enablement content flow


This discussion of how analytics enablement can be a vital part of your sales enablement strategy has surfaced an important concept: information gathered by marketing about the buyer should inform downstream sales activities. This notion of upstream/downstream information flow as part of the sales enablement process is important and points to the necessity of good sales and marketing collaboration. Given this imperative, I’ve been thrilled to see the massive uptick in marketing’s involvement in sales enablement over the past few years. That said, many organizations still have work to do.

A while back, I was in a meeting with the CMO of a large, enterprise software company where it was clear that he understood the value of sales enablement. What wasn’t clear was how much he understood the necessity of close collaboration with the sales organization to do it right. He did a wonderful job articulating how much work had been done by his organization to understand the buyer’s journey, so that they could map marketing content to that journey to ensure buyers were getting just the right information when they needed it. Referencing this work, I asked him if he was similarly mapping sales enablement content to the seller’s journey. He literally put his hand to his forehead. “You’re just throwing it over the wall, aren’t you?” I asked. “Yup,” he admitted. He is far from alone.

The information that marketing provides to sales as part of the sales enablement process will be of significantly higher value if it is delivered based on an understanding of the sales process. Just as the different stages of a buyer’s journey require different types of information, so too does the seller’s journey demand relevant and timely content delivery. In my next post on “What is Sales Enablement?” I’ll share a table Rich Vancil and I created to outline some sales enablement process roles for marketing and sales. I offer the tale above and that table in the hope that they can facilitate and foster an important dialog on how sales and marketing can partner to improve sales enablement content delivery.

For information about Sales Enablement, please contact Keith Gaffney - kgaffney@idc.com

 


There is No Silver Bullet When It Comes to GDPR in the Channel

The General Data Protection Regulations (GDPR) will be enforced from next May – and everyone in the technology industry is talking about it. So much so, the topic even took center stage at Microsoft Inspire – its massive annual global partner conference – earlier this month.

(This was especially interesting as the company and the event are US-based, so this dispels any myth that it only applies to European companies).

But unfortunately, the amount of people talking about an issue does not always directly correlate with the level of understanding there is about it. GDPR is a complex topic, and the regulations themselves come in the form of a lengthy legal document. However, if you thought GDPR was confusing by itself, it can be even more so when considering it in the context of the channel.

My role at IDC is to focus on Channels and Alliances, but we have a huge resource dedicated to all things security, specifically GDPR. Our GDPR experts provide detailed coverage of the nitty gritty details when it comes to the regulations, but in this blog, I wanted to bring it to life from a channel point of view. In its simplest and most basic form, the role of "data controller" is the data owner, for example, a bank, which owns data it collects from its customers: names and addresses, financial information, and so on. The bank determines the purpose and means by which the customer data is processed, making it a controller by definition. Any third-party processors of that data – a technology provider, for example - do so at the instruction of the controller, and become a "data processor". Simple, right?

But if that third-party data processor (the technology firm, in this example) uses that data for other purposes – monitoring or optimization, for example – they too become a controller, because they are determining what happens to it. The crucial distinction here is that, in this scenario, the third party does not become the data controller instead of the first data controller (the bank), but as well as. This is a concept it is essential to understand when it comes to channels, because there are significantly more layers of complexity added on top of an already dense topic. The nature of the channel means that there are multiple companies involved in the provision of a technology solution to a customer. Hence, there are many companies which could have access to, or control over, a customer's data.

A customer may work with one or two partners, which in turn could work with a distributor or two, and multiple vendors. The partner may even work with other channel firms in a partner-to-partner relationship, all on the same customer solution. So if the worst should happen and a breach occurs, there are many directions to which the finger of blame could point. This level of complexity has got the channel talking a lot over the last 12 months. Many companies are looking to position themselves as trusted advisors when it comes to GDPR, and many are re-packaging their solutions to speak directly to this challenge. And quite rightly so – customers need help.

But what it is so important to stress is that there is not one silver bullet when it comes to GDPR. No single company can make a customer bullet proof, and no single customer can completely outsource all GDPR-related responsibilities to a third-party. So what can you do? There are a number of steps which can be carried out by companies at all levels in the channel to ensure they are on top of the upcoming changes.

Advice for vendors

1) Gain genuine understanding into which parts of the channel have responsibility for what

2) Collect and retain evidence

3) Ensure your customers and partners know what you can and cannot provide

Advice for partners

1) Ensure you fully understand what your role is when it comes to customer data

2) Review customer contracts and retain documentation of having done so

2) Seek legal advice

Advice for customers

1) Accept that you're responsible for your customer data

2) Fully audit customer data

3) Consider data minimization

For further reading, please check out  our recent market perspective: The Impact of GDPR for Channel-Centric Vendors

For more information about IDC's Channels & Alliances research an overview of the program is provided here.


Artificial Intelligence Can Transform Insurance Industry for Good

Sabitha Majukumar (Senior Research Analyst)
Philip Carnelley (Associate Vice President)

Insurance industry is currently on a digital mission to offer contextual and value-centric products and offerings to its customers driven by the change in customer and market expectations, technological disruptions, and the emergence of new kinds of competition: Worldwide Digital Transformation Use Case Taxonomy, 2017: Insurance

We believe that cognitive/AI systems can present effective options to help accelerate this transformation journey to achieve this digital mission and stay competitive.

Cognitive robotic process automation [RPA] is one of the most prominent applications of cognitive technology emerging in insurance. With the integration of cognitive technologies, RPA is making its way to the front-office operations of insurance organizations (both carriers and intermediaries). Cognitive RPA, also known as intelligent RPA or simply intelligent automation in the form of robo advisors, chat bots, and virtual insurance agents, is expected to have a significant impact on customer engagement roles in the industry in the coming years.

Some insurers are taking the lead to leverage Cognitive systems and Cognitive RPA to transform certain aspects of their business:

  • U.S. Insurer Allstate has employed a chatbot called the Allstate Business Insurance Expert (Abie) to help insurance agents in the quotation process for complex insurance products.
  • An online insurance agency called Insurify has employed a virtual advisor called Eva to speak to its customers.
  • Grange Insurance, Nationwide and Safeco have partnered with Amazon on its cloud-based virtual assistant device to help customers find local independent agents and provide information on insurance products.
  • Chinese hometown search engine Baidu uses Artificial Intelligence systems to discover patterns that can be used in insurance underwriting.
  • AIG has invested in a startup company called Human Condition Safety to offer a solution that combines wearable technology with AI to track workers’ safety in factories.

These examples reflect a certain optimism in the industry currently towards the technology. Insurance organizations can leverage cognitive systems and cognitive RPA to improve customer experience, decision making, and operational efficiencies.

Most incumbents deal with large amounts of repetitive and rule-based tasks which use structured data inputs. A good starting point would be to automate these tasks to enable a reduction in cost and error rates and improvement in productivity and efficiency. However, in the past, this has often proven difficult, or not cost-effective, due to the inflexibility of previous generations of the technology: they are unable to cope gracefully with exceptions, and are very sensitive to changes in the systems, inputs and outputs, implying high levels of maintenance. Intelligent systems are more robust in the face of change and exceptions. Therefore, as a next step, organizations can adopt intelligent systems to leverage both structured and unstructured data from different internal and external data sources and transform the experience of customers and workforce across various lines of business such as auto (motor), home, travel, and commercial insurance.

If used the right way, Cognitive and Cognitive RPA can help transform insurance business functions like Customer Engagement, Insurance Sales and Customer Service, Underwriting and Risk Management, Claims Management, Fraud Handling, Marketing and Proposition (Product) Management, Regulatory Reporting. To effectively reap the benefits, insurance organizations need to have a clear strategy as well as the right skills and partnerships in place.

IDC has recently consolidated its findings and guidance on cognitive systems in insurance in the IDC Planscape Implementing Cognitive Systems in Insurance Organizations. This report aims to help business and IT executives understand what cognitive systems are, why they are relevant, and how they can be used to improve customer experience, decision making, and operational efficiencies across various business functions. The study also helps organizations build the business case and a road map to implement the technology.

IDC will be closely following this topic and its impact on different industries in the coming months. For an overview of the current and planned deployments and spending plans for AI in European financial services industry, check out our research Artificial Intelligence: From Science Fiction to Business. This is aimed at technology buyers to help them identify trending themes around AI, machine learning, and cognitive systems and compare their AI strategies against industry benchmarks.

Watch out for some interesting discussions around analytics and cognitive computing in the banking and the insurance industry in our upcoming Financial Services Forum.


Zero-Rated Mobile Data Spreads, Despite Questions of Net Neutrality

John Delaney (Associate VP, European Telecoms)

Zero rating means that an operator does not charge its customers for network traffic when they use specific internet services. In their search for ways to build competitive differentiation in a mature market, mobile operators are increasingly attracted to zero rated data for popular services, despite concerns in some quarters about compatibility with net neutrality.

Several European mobile operators have announced such offerings, most recently:

There is clear potential to construe zero rating of mobile data as a violation of net neutrality, if the provider of the zero-rated service is paying the mobile operator. “Sponsored data” offers have sometimes fallen foul of regulation on these grounds. But the conflict between zero rating and net neutrality is less clear if there is no direct payment involved. Other factors can also make the compatibility of zero rating with net neutrality more debatable, such as when the operator can claim it is being introduced for network management, or when zero rating is for a limited period.

By bringing zero-rated data offers to market, European operators are not only using a powerful differentiator, they are also pushing regulators to rule more clearly on what is not allowed regarding zero rating, so that anything else can be taken as permitted. It is instructive, for example, to consider UK regulator Ofcom’s explanation of its decision not to block the zero-rated Facebook Messenger/WhatsApp offer launched by Virgin Media in late 2016. Relevant factors included Virgin Media’s market share, the limited likelihood that the offer will stop people using non-Facebook messaging services, and assurances from Virgin that it is seeking similar arrangements with other messaging service providers. (For fuller details, see page 9 of the Ofcom report Monitoring Compliance With The EU Net Neutrality Regulation.) It seems reasonable to conclude that Three and EE were emboldened by Ofcom’s ruling when they decided to introduce their own zero-rated offerings. EE, for instance, referred during the launch announcement for its Apple Music offer to being “open to other service providers.”

IDC believes that although national regulators do not seem minded to block zero rating per se on net-neutrality grounds, mobile operators still need to exercise caution when introducing zero-rated data. The tactic has inherent limitations. In most cases, we advise operators to introduce zero rating clearly as a limited-period promotional offer. That way, not only are operators less likely to fall foul of regulation, but they are also able to gauge the impact of zero rating on their networks, customers, and revenues before considering whether to extend the offer, or to make it permanent.

If you want to learn more about this topic, or have any question on European Mobility, please contact John Delaney.