I was trying to write a title as pompous and with as many buzz words as possible and I do believe I’m close. Who knows we might even get featured on TechCrunch with these ramblings on how “big data” is enabling the ultimate phase of the B2B sales & marketing revolution…
Over the past few weeks at MadKudu, we’ve run a thorough retrospective on 2016 to flesh out what we’ve learnt, which hypotheses were validated, which were proven wrong.
The exciting learning is that we’re onto something big, something HUGE!
We’ve validated the fact that lead prioritization enablement was commonly sought. But more importantly we’ve realized that lead scoring solutions as they exist today are only duct-tape on a broken process. Since companies aren’t able to handle personalized onboarding at scale, they reduce the scale by focusing on a subset of leads to manually personalize the experience for. Welcome to the world of the inbound SDR. MadKudu is set to change this and bring us one step closer to completing the marketing & sales revolution by operationalizing personalization (channel, message…) at scale.
In essence the main actionable learning is that operationalization is 10x more valuable than enablement. It’s actually a completely different sport.
The Sales & Marketing Revolution
The term revolution is mainly used to describe an overthrow of an order in favor of a new one. But the root of the words tie back to the concept of going full circle. So when we talk about the sales & marketing revolution we mean we’re getting back to a previous state. While we’ll dedicate a specific post to this topic, a high-level history of marketing would go as such:
– Before the industrial revolution, people bought from local stores and suppliers. This was the era of one-to-one personalization of the product to the customer’s needs.
– The industrial revolution changed everything, the product was now king. Our newly discovered ability to mass produce meant we needed to find ways to ship these products. This started the era of the marketing mix’s 4P (product, price, promotion, placement) in marketing.
– In more recent days, the rise of the internet 2.0 marked the rise of the SDR. With online products being available for billions of people and marketing strategies still focusing on bringing in as many prospects as possible, there was a new need to qualify potential customers.
– The “big data” revolution. Data science has started powering personalization and relevance at scale in eCom marketing for a few years now. Amazon led the charge with its recommendation engine and many companies have since then applied data science to make the B2C sales experience more relevant (at AgilOne, we did a lot of this). The shift from the 4Ps towards the 4Cs is another illustration of this trend of putting back the customer at the center of marketing activities.
What “big data” brings to Sales
There is a common misconception that big data equates huge quantities of data and thus is more appropriate for marketing than sales and for B2C rather than B2B. But there are really 3 aspects to big data:
– massive data sets (high volume)
This is what companies like facebook, google deal with. We’re talking trillions of records of data to process. The main challenge here is scalability and is only seen in B2B2C or B2C companies.
– fast data (high velocity)
This is what real time analytics systems deal with. Recommender systems, trading algorithms are great examples of systems dealing with high velocity data.
– complex data sets (high variety)
Here’s the least sexy and known aspect of the lot. B2B companies generate big data with customer records coming from sales data, product usage, customer records, support tickets… While real-time analytics and scalability are challenges the hard nut to crack is the identity layer or combination of all the information in a comprehensible data set. Machine Learning algorithms will only ever be as good as the input they are fed.
Why is B2B Sales broken
The final aspect has been ankylosing the B2B space and has thus become a great source of innovation. Companies are spending billions of dollars to get their data together (getBirdly, Jitterbit), stitching it together (leanData, AgilOne). The hardest part though remains in rendering the data actionable. This is where Big data can help reach the holy grails of sales and marketing: “personalization to foster relevance, at scale”.
Lead scoring tools so far have been built with this in mind. They leverage the multitude of data points available to automate -to some extent- the qualification historically run by SDRs.
BANT Qualification process:
B => mainly firmographic data to determine if the account would have budget for your top tier pricing
A => mainly demographic to determine how close is this person to having a budget line item for your product
N => mainly firmographic to determine if the account likely to be a successful user of your product or at least have a need for it
T => mainly behavioral to determine if the account’s aggregated behavior is indicative of a strong likelihood to purchase your product in the near future.
And so this is where big data has been helping so far. Lead scoring solutions have been doing a great job at getting SDRs to focus on a small subset of leads that they can then write personal emails to through bulk email solutions like Yesware or Salesloft…
Where this approach falls short is that sending emails manually don’t make them personal, let alone relevant. We all receive tens of emails like this every day:
From cartography to self-driving cars
A couple weeks ago, Guillaume Cabane, VP Growth at Segment, made a striking analogy between cartography and B2B sales. Cartography is the representation of the overall landscape of your leads. It is used to determines the routes you need to follow to reach your destination. This is your initial ideal customer profile analysis. The GPS is an automated way of telling how to get to your destination. This is lead scoring as we know it today. The self-driving car is build upon a GPS and executes the commands reliably and automatically. This is the future of B2B sales, the idea of a “software SDR”.
In essence, the great opportunity to seize in 2017 lies in realizing the era of the GPS as a stand alone tool is over. We are now heading into a world of self-driving cars.
Not only are we convinced about this, the early tests we’ve been running so far are encouraging. Our software SDR has consistently outperformed by at least 66% regular SDRs on the amount of qualified demos booked. Not only were we generating more meeting, we also free-ed up time for the sales team so they could focus on what they do best: adding value to prospects whom we’ve engaged with them.
Here’s to 2017, year of the true sales automation!
Image credit : A future lost in time