Mining Data to drive B2B Sales Leadership

This is the second article in our Data and Analytics Leadership Series published on Medium and LinkedIn where we spoke about three major areas where value can be unearthed, from a data perspective:

 1.      Driving B2B Sales Leadership

2.      Marketing-led Brand and Sales Transformation

3.      Digital Transformation of the Production and Shop Floor

 Let us look at the first area: How can data and analytics drive sales leadership (especially for B2B companies especially Industrial and Diversified Companies).

 A recent Salesforce study indicated that 57% of sales reps expect to miss quota[1]. Another HubSpot study indicated that salespeople spend a lot of time (55% to be precise!) creating new data[2]. This includes writing emails (21%), updating data (17%) and doing research (17%). Meanwhile, B2B sellers cited creating competitive differentiation (26%), gaining appointments (14%) and connecting with the right stakeholder (12%) among the top challenges in prospecting, according to a Richardson report[3].

 What all this research suggests is this. Sellers are spending lot of time in creating sales related data – and not enough time in using the data created (qualifying prospects and targeting leads) and creating data that can be mined (competitive intelligence and customer intelligence). This is backed by the last 15-20 sales analytics projects we have done. Data that Salespeople are creating (Emails, CRM Updates, Internal and External Research, Call and Meeting Notes, etc.) is seldom used to identify and connect with the right shareholder at the right time – because in most cases, sales leaders do not think this is valuable or do not know how to mine it.

Despite markets that are rapidly changing and evolving and tons of tools that make it easy to mine the data, there is simply little-to-no time to train and update salespeople. We need to dive right in and drive this change by picking up and getting a few wins. 

While it is true that big data technologies, inexpensive compute (GPUs) and machine/deep-learning have given sales leaders access to unprecedented amounts of data and computing power, allowing them to predict with a high degree of precision the most valuable sales opportunities, there are four major challenges that need to be tackled:

 1.      CRM Data Quality needs improvement

2.      Competitor and Customer Intelligence is missing or very spotty

3.      Lead Qualification and Targeting needs improvement

4.      Better Pricing Strategies are needed to avoid leaving money on the table

1. Improving CRM Data Quality

No matter what client you are assigned to, or what lead/prospect you need to search for, chase and convert – the bottom line is that you need to adhere to a set of sales-related data tactics. Salespeople spend a lot of time updating data in their CRMs and in exchanging emails – yes, emails are also usable for analysis. Yet, the biggest challenge when we get into a CRM Analytics project is the usability of that data.

 Usual data challenges that one needs to overcome are:

1. Text fields have all kinds of values (e.g. Loss-Reason, Product Category, Product Type, etc.)
2. Numbers that are entered in all kinds of formats ($, comma, words, etc.)
3. Emails that are just added to the CRM as an attachment
4. Documents that are uploaded
5. Not having the proper Social Media and Tools connect

Here are five steps to be taken, as a starting point:

1. Identify all text fields in the CRM that have more than 5-7 entries and see how they can be converted into a drop-down (except fields like Notes which are meant to be long form). Work with your CRM vendor or your internal IT Team (if it is an internally built CRM) to get this done.
2. Increase validation that is done on all Number/Currency fields within the CRM, and train sales folk to ensure that for example, number fields are entered in the apt numeric format, and data that is added going forward is clean. Design and execute a data enrichment exercise to cleanse historical data in parallel.
3. Most CRMs today have a feature to connect emails to said CRM. Enable it and incentivize your sales team to do that immediately. Encourage them by sharing that this sync will only help them reduce the effort they spend on capturing notes over time. As an example, sending a MoM (minutes of the meeting) will mean that the deal/contact is updated in the CRM.
4. Enable mining of key documents (SoWs, RFPs, Invoices, etc.) and connect with other internal systems (e.g. ERP) to enrich the data even further. Even identifying that an invoice has not been paid on time (even if you’re just using the name of the file attached) for an existing customer can be a warning sign that can remind your salesperson to pick up the phone and call.
5. Each customer is unique and would have preferred channel of communication (Email, Phone, WhatsApp, LinkedIn, SMS, etc.) Knowing their preferred channel and knowing what time of day would work best for a response is critical. Gathering intelligence from earlier conversations on response times and responses to messages on specific channels will enable better targeting customers at the right time.

This will be Step 1 in avoiding the below scenario!

2. Competitor/Customer Intelligence can be a Game-changer

Is this your strategy to counter the competition? And do you have customer data and insight, and using that, or relying on your gut?

Blindly attacking the competition and not knowing what makes your customer tick, can be disastrous. If your sales team is mostly working on sales qualified leads, the biggest loss-reason is going to be price and of course perceived value. While the sales team can and should be trained on enhancing the perceived value of your products, in a commoditized market, price does become a critical factor.

Sales leaders can gather intelligence about competitors and clients/leads/prospects, that help their sales team improve customer-focused messaging. Below are a few interesting examples:

1. For a Global B2B Automotive Auction company, we designed and built a competitive intelligence platform that gathers competitor intelligence (from multiple structured and unstructured sources), uses this data to calculate market-share by geography, gathers price related data to understand competitor pricing and recommends an ideal pricing strategy, and delivers insight via a set of Managerial and Executive Dashboards, to key stakeholders
2. For a HR Consulting firm that helps its customers hire people (full-time and contract), we created an intelligence solution to proactively identify roles that their customers were hiring for (capturing and analysing data from over 20 3rd party platforms) – along with gathering intelligence on profiles saved and shared with clients, by competing companies
3. For an Asian Micro-finance company, we helped them enrich their prospect data significantly using social media data, along with three 3rd party databases. This data mashup was used in a unique manner to recommend a targeting strategy – along with an integrated tool/web extension that allowed for outbound calling. This initiative led to significant improvements in their marketing campaign response rates.

Always know your competition! Copying them or not – that is a choice!

3. Better Lead Qualification and Targeting

The biggest complaint that salespeople have with marketing is that they do not get sales-qualified leads. Sounds familiar? A critical step that a sales leader needs to take in improving the sales pipeline is to get both sales and marketing into a room and get agreement on what qualifies as a Sales Qualified Lead (SQL). Once that is established, monitoring the quantity and quality of SQLs will significantly drive greater synergy between the two teams. Else, you run the risk of something like this happening.

The key to monitoring this is of course being able to get alignment on what are the criteria for a lead being a SQL and again, for that data to be entered into the CRM system. 

The biggest side-benefit to getting this data into the CRM of course is that an analyst can then look at the data on all the SQLs, including losses and wins and ones that are in-limbo, to get further insight into what works, what does not, and behavioural patterns.

This in turn can then help develop best-practices and help sales leaders qualify SQLs on the right kind of messaging, timing of the messaging and the channel to be used for messaging.

4. Better Pricing (a.k.a. No Money on the Table Please!)

B2B Pricing unlike B2C Pricing is very salesperson driven, with several factors allowing for a relatively high margin for price discounts. But, unless clear guidelines are set and the right metrics (profit vs. revenue) are set as goals, salespeople can end up giving away too much in order to close a deal. In fact, some of our clients might not find the below funny! In which case – sorry!

Tracking historical price changes before a deal is closed within the CRM system – this is a gold mine! This can help assess if the right pricing strategy was adopted in the past, and to track what customer segments are price-sensitive vs. value-driven. This in turn will help you assess what customer segments to focus on with what products, given the margins that each customer segment / product combination gives.

In addition, the right Pricing Analytics intervention has the following benefits, in terms of flagging:

• Salespeople who pitch low to meet targets or bonuses
• Customers whose discounting does not match the volume of business they deliver
• Products priced neither too high or low vis-à-vis competition and value delivered

In Conclusion,

Unless, you don’t want to be the above, you should look this as a three-part journey to driving Sales Leadership within a B2B organization:

• Improve quality of data in your CRM,
• Enrich internal data with external data, and then
• Improve targeting of customers with the right offers at the right time and the right channel

Here are some points to ponder, from a Sales Analytics perspective:

• How can improving CRM Data Quality give your analytics initiatives a boost?
• How can enriching competitor and customer data and combining it with internal (CRM) data be a game-changer?
• How can combining online (clickstream) data with ERP and CRM data work wonders for your sales efforts?
• Simple pricing strategies and initiatives to double your margins

 We will touch upon them (or parts thereof) in upcoming articles.

 That’s it, folks! Do share your feedback on this and we’d be happy to cover more.

Author Profiles:

Randhir Hebbar is one of the founders of Convergytics — Asia’s leading analytics brand (Global Brands Magazine). Randhir heads Data, Digital, BI and Products at Convergytics

References

[1] https://www.salesforce.com/blog/2018/05/sales-future-trends-research.html 

[2] https://blog.hubspot.com/sales/sales-statistics

[3] https://www.richardson.com/sales-resources/selling-challenges-research/