12 min read

Sidetrade is an organization that is on a mission to transform customer engagement in the world of B2B marketing with the help of artificial intelligence. With its own AI technology – Aimie – it’s now in a strong position to carve out a niche for itself in a market that shows no signs of slowing down.

What makes the company even more exciting for us at Packt is that they’re just a stones throw away from our offices in Birmingham. To get the lowdown on Sidetrade we spoke to CTO Mark Sheldon about the company’s evolution and what the future might hold.

Read the interview below…

Packt: Tell us a bit about your background and what you’re up to today.

Mark Sheldon: I started my career as a developer and moved into the management of a large technical team, at one of the ‘big six’ utility companies in the UK. Back in 2013, when the AI buzz was in its infancy, I co-founded a predictive analytics software company called BrightTarget. It was clear there was a better way for B2B organisations to gain more value from their data, and cloud computing and machine learning were clear market changers. In 2017 BrightTarget was acquired by Sidetrade and at this point I became part of their technical leadership team, with the goal of making Sidetrade an AI-driven company.

More recently I moved into the Group CTO position (as part of the global leadership team), responsible for more than 85 staff. Sidetrade has a total of 250 staff across six offices in Europe, with expansion planned in 2020.

The AI boom and its impact on the B2B landscape

Packt: Gartner predicts that this year 30% of B2B companies will use AI to augment at least one of their primary sales processes. What’s your take on this?

Mark: Yes, only 30%, so this market is still just emerging. Although machine learning has been around for decades, there’s still a lot of confusion around AI in many B2B organisations, mostly caused by all of the market and vendor hype. Very few have successfully deployed machine learning and are able to demonstrate value. However, for those that have, the potential for commercial gain deploying AI is huge.

The most common processes impacted in sales & marketing are those which involve interactions with customers or prospects at scale; where the decision making of a human can be augmented or improved. e.g. Identifying customers most at risk of churn, customers with the best opportunity to sell more product or prospects with the highest propensity to become a customer.

AI really allows sales & marketing teams to optimize their time and marketing spend.

BrightTarget and Sidetrade

Packt: You co-founded BrightTarget which was acquired by Sidetrade in 2016. Could you tell us a little bit about BrightTarget?  

Mark: BrightTarget was founded in 2014, on the principle of helping B2B organisations deploy AI without the need for expensive and hard to find data scientists. We invested significantly in automating the process of data loading, processing (feature generation), model building and monitoring. We achieved strong traction with some large enterprise accounts and were recognized by Forrester as a “Strong Performer”.

Packt: How did the acquisition come about?

Mark: At this time [when BrightTarget was founded], Olivier Novasque (the Sidetrade CEO and founder) had a clear vision to transform Sidetrade into an AI-driven business. So the acquisition of BrightTarget in November 2016 was a natural fit with the ambitions of Sidetrade and their goals. This has proven to be a great move with the launch of Aimee (AI engine) which has contributed significantly to the subsequent revenue growth following the acquisition.

Aimie: Sidetrade’s AI technology

Packt: Tell us a bit more about Aimie. How does it work? What’s the thinking behind it?

Mark: Aimie is Sidetrade’s propriety AI technology that helps our customers augment their daily experience within our products. For example, Aimie helps every cash collector make the very optimum collection decisions, even if they have only joined the company two weeks ago! This AI technology is at the heart of our SaaS platforms – Augmented Revenue (helping B2B organisations to manage their Revenue; including managing revenue at risk and finding opportunities to grow revenue from existing customers) and Augmented Cash (again, helping B2B organsisations improve working capital by better cash collection).

We also have an unrivalled data lake built up over 20 years. We now have 230 million B2B payment experiences, totaling sales of over 700 billion Euros [£621 bn] which we train our AI on, and enriches our client’s own data. More good quality data for AI to train upon means for better predictions and outcomes.

For example (reported in Fortune and Forbes), one of our enterprise clients is Manpower, one of the biggest recruitment firms in the world. With an annual income of €4 bn per year, Manpower France collects 1.3 million receivables from 80,000 companies. To handle this volume, and increasingly complex payment procedures, Manpower’s finance department started using Sidetrade technology in 2013, and introduced Aimie in 2018-19.

Manpower started Aimie off with two customer portfolios for a period of two months. Aimie analyzed what worked before for Manpower, directly executed automatic follow-up actions, and established which past-dues to target first. She considered available resources (staff hours, workloads) in order to take optimal actions.

Encouraged by the results, Manpower ramped up their use of Aimie. Within four months, Aimie was managing nearly 60% of their single-site customers, which represents over 5,000 accounts, and nearly 10,000 follow-up actions per month. Manpower has over 700 payer centers to manage, making it impossible for a manager to call all the debtors in their portfolio. Aimie helped them decide which customers to contact first.

After nine months of testing, the results were clear: with support from Aimie, effectiveness of recovery actions grew 12%. That’s a good improvement in cash collection which boosts working capital, vital for business.

Sidetrade’s data science team

Packt: Sidetrade has a data science team, what is it and how does it function? How does your team of data engineers, data scientists work in tandem with the product teams to create AI powered B2B solutions for customers? Do they also work on customized solutions?

Mark: Dr Clement Chastagnol (PhD in AI and robotics) leads our data science team. We currently have a team focused more on research topics, who really push the boundaries on some of the latest aspects of AI. However, the majority of our sata scientists work directly within product-led squads (with a mixture of different data, application & ops engineers). The reason for this is to ensure we deliver actionable AI/ML into our products on a regular basis, to ensure we are customer (therefore product) focused.

As a SaaS company with 1000’s of customers/users, almost all of the work we do is to improve our overall products, and adding features that benefit the majority. This also applies to data science, although we have a very advanced M/L platform which allows us to automatically build and manage 1000’s of M/L models, that are often client-specific.

In terms of research, each year we work with the French Government’s business ombudsman, to research and produce an index report of all B2B business payment disputes, including figures by industry, and length of delay. This involves our data scientists analysing over 9,000 French customer companies representing, 91% of large corporations and organizations with 250 to 5,000 employees. The data analyzed covers over 2.8 million invoices totaling €12bn.

Also as part of our research work, we have received funding from the French Government, EU Commission agencies, the French national agency for research, and the DataAi Institute on the following projects:

  • Eurofirmo, which is an index of all 26 million businesses in the EU and Britain, including headcount and revenue which has never been done before.
  • Re-search Alps, which is a collaboration with academics from four universities that aims to track all research-active research institutes across seven European countries. It records their research projects, funding, publications, patents, and other academic output.
  • Dirty Data: Two research axis are funded. One revolves around dirty data integration, funded by the ANR (Association National de Recherche). The other strives to develop new techniques to analyze incomplete data. It is funded by the DataAI institute. As part of this project, we’ve worked with Gaël Varoquaux (ML Researcher & creator of Scikit-learn) which has been great.

Alongside all these projects, the team has recently worked with Facebook Research on the topic of data drift, as well as publishing research in journal papers, academic conference attendance and presentations, support for PhD students, hackathons and guest lectures at universities.

Developing new talent in the AI space

Packt: Sidetrade recently launched The Code Academy, what is it? How can developers take part in this initiative and how will it benefit them? What are other key initiatives by Sidetrade?

Mark: The Code Academy is designed to develop the next generation of AI talent and is important for Sidetrade to maintain its position as a leading AI powered customer platform. The Code Academy, which was piloted in 2018, is part of Sidetrade’s commitment to providing engineering skills and jobs for young people in the Midlands, to keep the UK at the forefront of the AI industry.

It’s a new, rapid approach to training and job creation. We welcome trainees with computing and non-computing backgrounds who can demonstrate ability and passion for technology. It’s rapid, as we design and deliver the academy in-house over four weeks, with a lot of support from senior developers in the team. We train for job roles, rather than just impart coding. And it’s offered without cost to the trainee, so money isn’t a barrier.

At the end of four weeks the trainees are given a challenge, and asked to present their work to an audience of senior staff. Academy modules include:

• Becoming familiar with Git
• Setting up VSCode for .NET & Web development
• How to load a relational data set through pgAdmin (CSV)
• Learning how to write TSQL to analyse and find trends within a data set
• Learning about the concept of & develop a basic RESTFul service
• Introduction to angular (using http://angular.io/start)
• Learn to connect all layers of the stack
• Use Kanban (Trello) to manage projects
• How to define an MVP

In 2018 we trained 10 people and offered software and data engineer roles to three. In 2019, we revamped the academy, making it much more practical, and selected 12 trainees from 50 applicants. The quality of the talent was so good we offered five trainees data and software engineer roles with our professional services and R&D teams.

Expanding the team

Packt: You’re about to move into a new, much bigger office in central Birmingham. What are your challenges in terms of expanding the team? Can you elaborate more on the challenges faced by the team in terms of working with AIOps.

Mark: That’s right, we’re going to open a new Tech Hub that will house a much bigger team of data and software engineers working across the full stack. We’ll also run our 2020 Code Academy from the hub. A special launch event, Together for Tech, will make the opening official on 27th February 2020, with VIP guests, tech and business stakeholders. We’ll also be announcing a major investment in R&D and jobs creation. There is huge potential for Birmingham to become a tech powerhouse within Europe.

The challenge for me is hiring enough senior level tech professionals. These people are needed to lead teams, develop staff, and keep pushing the boundary of what we can do. There’s overall a challenge to hire enough qualified professionals for the tech sector, and that is more acute at the senior levels. I think there’s a temptation for experienced tech types to head to London or even America, so it’s a challenge for the region to retain great talent.

The team has spent a lot of time on ‘AI ops’, which has emerged in the past three years. So, the other challenge is how do we actually productionise all of the models and data engineering that our team and platform is producing. How do we deploy & run them in production? How do we monitor them? This is all about managing Machine Learning models at scale.

For me, the sheer volume the team have to deal with is the biggest thing. We train thousands of different predictive models for different clients, and they are changing all of the time in terms of the data they are trained on. So actually, building workflows and processes to help monitor those in production at that kind of scale without having to scale the team in proportion is probably the biggest challenge.

The future of AI and automation for B2B marketing and sales

Packt: AI is a really broad term. It often gets used interchangeably with machine learning and deep learning. Do you think this confusion is risky or dangerous? Do you think people should simply stop talking about AI in favour of machine learning and deep learning?

Mark: I think we’ve reached a point where AI has become a buzz word and a catch-all phrase. I think we can and should start being more sophisticated about what we mean, it’s a work of education.

From a vendor and business point of view, AI is no longer a differentiator as everyone is talking about it, so it makes it harder to stand out. But as decision makers become more educated on the topic, it’s clear which vendors have the expertise and depth of data to deliver true AI-powered solutions.

Packt: What do you expect to come next in the B2B Sales and Marketing space? And how is automation of this space likely to impact other industries?

Mark: My prediction for the next big thing to come in the AI space would be a major breakthrough in Quantum computing by either Google or one of the startups specializing in the field.

In the B2B sales and marketing space I think the next step is just wider adoption and trust that AI can augment or even outperform humans. Most businesses will need to go through a cultural and often organisational shift that is required to get the full commercial benefits out of AI.

Thanks for taking the time to speak to us Mark! We’ll be watching Sidetrade closely over the months and years to come. It’s also great to see such an exciting and innovative company growing in Birmingham, right near the Packt office.

Learn more about Sidetrade: www.sidetrade.com