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I have received lot of encouragement in my last blog post hence I am excited to share a new post.In addition to typical Customer Success activities lot of my interactions with customers involves Sales enablement .I currently manage our Tier 1 customers in the West Coast so this B2B Enterprise focussed, think of the dynamics in a $1M+ ACV discussion.This highlights some of the tactical execution activities when you are making a pitch about your Big Data Products or services and trying to convince clients
Here are four tips to build your Big Data sales pitch for convincing clients:
Build a Business Case specific to Big Data
There are some challenges associated with selling big data through a business case. This is a new market and not many proof points or metrics are available to leverage. So one would have to a plan right from scratch. A business case for big data will have several benefits mentioned but one needs to focus on a single problem and some handful of metrics to build a business case. Quantify these items and leave the rest. With metrics that you bring to the table, it is enough to prove that it is worth pursuing.Also, with Big Data, you can focus on how analytics would aid your decision-making process with a case study reiterating your point. A business case gives a better insight into the actual workings of the solution.
Identify a sponsor!
Identify any of your business executives to be potential sponsors. Start out with a pressing business issue that big data technology can solve. Look for a sponsor who is dynamic and knows the business. After identifying that individual, book a short meeting and review the ideas if the technology is meeting the strategic priorities. Send in an agenda and an email summarizing the value proposition of Big data and its differentiators. A head start on the introduction would surely help you to have a real conversation with the client. Have a short email with a good product and service pitch. This part would help you understand whether your pitch works! Don’t share everything you have.
Capture metrics and narrate a story
Many projects display statistics to create shock or surprise. Do not fall into the trap. Instead use few metrics that can be measured using real scenarios related to the business case. By reporting a single idea again and again through a metric, it gets ingrained in the business minds.Tell a story about big data technology and its use to improve fraud detection or any other purpose, since stories always sell initiatives.Big data technology has huge potential but in order to drive adoption, one must evangelize big data to the business community, specifically in business terms.
Know your product or service thoroughly by listening more!
The only thing worse about not doing a thorough research about a client is to not know about one’s own business which means lack of knowledge of what Big Data is all about. Get answers to the technical or business-related queries, and also about the competition or market. Know about the stuff and always add value to the conversation.
Conclusion
Additionally, it is important to do less and to-the-point talking and concentrate on listening. It is very easy to start your own story once the meeting starts—but it is necessary to prompt responses and listen to them first. Getting your clients in to the comfort zone is the first step and listening to their problems will land you with the best opportunities to crack a sale. Avoid building the meeting around the presentation you have prepared or the sales script, but around the client’s business and your take on why your Big Data solutions can help with adequate pointers.
Here is PROS 101 or “PROS for Dummies to illustrate” what we do following some of the techniques from above
CEOs are always looking for a competitive edge in their sales execution. It’s no longer enough to rely on gut instinct and experience when selling.They need the power of big data analytics – an exciting new area to drive sales growth that most companies are only beginning to explore. Wouldn’t it be great to know which opportunities were most likely to close, which offers were most likely to sell, and which prices were most likely to win? At PROS, we give companies the insight to answer those questions and the guidance to turn those insights into sales growth. In short, we shift the odds of winning back in their favour. And, we’ve been doing it for nearly three decades.
In my current role at PROS I execute sales strategies to increase our revenues. I work closely with our existing customer base and show continuous vale in our products.
PROS (NYSE: PRO) is a big data software product company and our software Products are used by our customers for tasks such as customer segmentation , price guidance, forecasting demand, optimizing inventory allocation, modelling price elasticity and monitoring transaction profitability.
Here are some tips to take the right sales approach for selling Big Data applications. This applies whether you are trying to sell services, products or show value in an existing a Big data application.
Don’t start with data or the technology, start with your strategy and business objectives. Once they are defined, isolate big questions and then refocus your data requirements rather than beating around the bush about endless possibilities.
Do not show mind-boggling investment figures on the outset but get your customer to be clear about what data they will need and help them build a simple dataset by being specific about the information. Do it in phases.
Decision-makers in a company love to represent their business through spreadsheets, and graphs. Likewise, prepare statistical charts and graphs that share new insights about how BI can be boosted with Big Data implementation within an organisation. Give examples on how every manager searches for information and collates it before using it, but Big Data does that for you in an automated manner.
Big data is all about being smart enough to make the most of information. Presenting a host of figures on varied aspects of the business is tough, Message it in way saying Big Data analytics can make sense of the trends efficiently and thus interpret the real world better to make smarter decisions.
Try to make our prospects equate Big data as a trusted reservoir, and not as a landfill site where data is filtered and purified for capacity and dynamic scaling.
If you are going to pitch for Big Data to your customers, you need to convey the true business power of big data, prepare the right explanations and pitches to make a convincing case for Big Data implementation within the organization.
There is lot of debate on where should Customer Success reside in an organization. During my interactions with other Customer Success practitioners I often discuss the following questions.
Should it be in Sales or in Professions Services or should be on its own?
If they are in Sales should they be commissioned on Renewals?
Customers today choose solutions based on relationships and products that add value quickly, and continue to add value over their lifetime.According to me the following summarizes the role of Customer Success Manager very well
To grow existing customer relationships by insuring a high level of customer satisfaction, jointly developing long-term strategic partnerships, while exploring opportunities for continued growth.
Growth and Sales always go hand hence I recommend Customers Success strongly aligned with the Sales organization. All Customer Success Managers should be commissioned for any activity in their account.
I suggest Sales introduces the Customer Success process early in order to set expectations with the client. Introducing Customer Success into a customer engagement during the presales process might not be appreciated by all Sales people at first, but they’ll see the light in the end.In addition to Sales, CSMs should have a thorough knowledge of the product features, common issues and adoption barriers and customers should view them as product experts.
The goal is to develop an a long-term strategic account plan for each customer and Insure customer is fully leveraging their investment
Malcolm Gladwell explores the Customer Success Tipping Point at Pulse 2014.
The most expensive software is the stuff you don’t use. And that isn’t just because an implementation may have gone badly. It may be because there is no impetus for change in the organization. Because operational change management is such a big part of using new software, it is important to pick the right KPIs, monitor them and use them to make constant improvements
Benchmarking program is a way to keep customers on track, not only technologically but also with respect to change management.
As a customer Success practitioner you should partner to select, measure, improve upon and report on the right KPIs throughout the life of the customer , we can ensure mutual success and keep the partnership going for many years. The initial goal is to set an operating baseline that we can use to track a customer’s performance over time.
These are typical domains in the journey in a customer’s life as it progresses
Configure, price and quote (CPQ) application suites provide an integrated set of software applications supporting the configuration, pricing and quote generation activities that accompany solution and negotiated selling. To Read More about them go here
I have seen 2 Products that offer CPQ solutions , having worked at Apttus for 16 months and now at PROS. While I really respect Apttus and I wish them all the best ,after looking at what PROS CPQ offers I would not recommend customers Apttus unless they have some specific use cases.
As a Customer Success Practitioner I always believe in adding value to my customers and companies that need a Quote and a Proposal Generation tool should look at Apttus. In addition if they have a strong preference for a 100% native Force.com solution then Apttus would be a good fit.
However based on my own personal assessment ,these are some of the deficiencies (this is as of Nov 2014 and might be addressed by them in future releases )
Product Configurator Concept of Bill of Material very elementary. Approach is that of a basic shopping cart bundle.
Pricing Rules Management Cannot handle complexities such as taxes, route determination for logistics costs and other such scenarios
Rules Based configuration Rules-Based Constraint Engine creates a more costly implementation and requires a lot more administrative support
Analytics The lack of a comprehensive data model to accommodate bills of materials, versions and detailed product masters make it difficult to provide in depth analytics
Integration with ERP Relies on Salesforce APIs for interfacing with backend systems. Data model too simplistic to handle the various relationships of a product, its versions and BOMs
Since I work with my customers at PROS and help them outperform in their markets by using big data to sell more effectively it is natural I would use data to drive my decisions and have a data driven approach to Customer Success. Through some images and some descriptions I have tried to capture. Idea is to make renewal a “non-event”.
1.You need a combination of quantifiable to leverage as well as rely on your gut-feelings. Think of cooking a dish with a recipe but improvising by constantly tasting what you are cooking and adjusting.
2.Relationships are most important at higher price points, and data is the foundation for establishing powerful and deep relationships.
3.The data should be used to understand the value your customers are gaining from your application and what success means to the customer
4.By analyzing the data and highlighting patterns of trouble that could be churn indicators you can focus on at risk customers.
5.The Data that is collected and can be shared with customers and used in customer engagement in the form of monthly scorecards, quarterly business reviews, insight emails, and in-app messaging.
