Predictive Analytics in B2B E-commerce: A customer acquisition example
As “Business Manager E-commerce” I work daily with new trends and strategies to improve and optimise the buying experience of our B2B customers.
There is one trend that Business Managers cannot avoid in E-Commerce these days: the systematic use of data to optimise product and sales strategies.
Business Manager in E-Commerce – What exactly do you do?
I work for a global construction company. Around 7000 employees spread over 160 sales and logistics locations in 70 countries work every day to supply our customers with products so that they can build high-rise buildings, bridges, tunnels and other fascinating structures.
Running a B2B online shop to give customers in this industry the opportunity to purchase materials online for their construction projects is a worldwide first. Currently, we are the only ones in the industry to sell such products online.
A B2B online shop from in construction industry? Tell us more.
A novelty is this digital channel not only for our enterprise but above all also for our customers. Customers are used to calling our sales representative for orders or sending an e-mail to them.
Due to the limited human resources in sales, it is not possible to support all construction companies of the world personally and to acquire new customers – on top of that. Many “white spots” on the map show the still unused potential. As part of my part-time studies at the Austrian Marketing University, I wrote my master thesis on the possibilities of acquiring new customers in B2B E-Commerce with the help of predictive analytics.
If Amazon, Netflix, Spotify and other B2C counterparts are worldwide thriving with predictive analytics, it must also be possible to use this technology to win new customers in the B2B sector!
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Please give our readers concrete recommendations for action:
First: the technology is excellently suited to succeed in the fastest growing online segment – B2B E-commerce. After numerous expert interviews with internationally renowned B2B sales professionals and renowned experts in the field of predictive analytics, the following procedure for acquiring new customers with the help of predictive analytics was identified:
What is true offline is even more accurate online!
Measures for the acquisition of new customers according to the “watering can principle” cost much money and are usually not target-oriented. Hardly any company can afford to take global marketing measures to reach entire industries. In a globalised world, it is not possible to target everyone. It is more important than ever to address the right customers. Technologies such as predictive analytics can help you identify and target the right customers.
Leverage existing resources.
Nearly all companies sit on a treasure trove of (data) but pay little attention to it. Use your internal data available and link it with external, publicly accessible information. Sector-specific organisations or national institutions such as the Austrian Chamber of Commerce or the Chamber of Industry and Commerce in Germany can serve as sources. With the studies, statistics and key economic figures available there, your data can be expanded to identify growth markets and trends at an early stage and to derive appropriate measures.
Trust the power of data.
The use of your data, including externally enriched datasets, quickly results in unmanageable mountains of data. Do not rely exclusively on your instinct for the evaluation. Use technologies that support you in the review.
Predictive analytics makes it possible to generate meaningful insights from data, insights that may surprise you, insights that will help you to identify potentials in the acquisition of new customers, to derive sales strategies and to set sales priorities correctly.
Technology-supported evaluations can help you find out in which markets untapped potential lies dormant, which companies are highly likely to address your products and services, where existing buyers come from and which characteristics they have (e.g. company size, sales figures, local vs global companies, among others.). By evaluating all these data, you get valid statements, which can optimise the acquisition of new customers and list promising potentials.
Get the best out of the offline and online world.
Use different channels to win new customers by targeting the previously identified customers. Find out how and where you can meet potential new customers. If you visit these fairs, can they be targeted online (e.g. on platforms such as Xing, LinkedIn.) or is it more target-oriented to merely access the listener and present yourself by telephone? By clustering into different communication channels, companies can gather existing sales resources purposefully to target specific customer segments.
As already mentioned, many companies sit on data treasures, which are, however, hardly noticed. The “respect” for new and unknown technologies is too high. Be open to new technologies! Many experts have confirmed to me in the interviews that predictive analytics projects in companies often do not come about, only because of the fear of contact with the technological possibilities.
The fear of the unknown is too high, the uncertainty too great. However, anyone who deals with the topic of predictive analytics in the same way as I do will quickly recognise a methodology behind the buzzword. This methodology only captures and combines existing data and enables evaluations to be made to make decisions and derive strategies from facts and figures.
Predictive analytics is not rocket science. It is not a black box in which opaque processes happen, and finally, bits and bytes are output that salespeople can hardly understand. Predictive analytics helps companies to operate successfully in the market and to identify sales opportunities.
Therefore, anyone who is prepared to get involved with the new technical possibilities and who is afraid of the new technologies has a good chance of generating real added value for his company and of supporting her sales team regarding customer acquisition and development.
And don’t forget one thing: if you don’t make optimal use of the existing possibilities in the form of data, algorithms and targeted evaluation options, your competitor will.
Thank you, Mr. Haunschmid, for these useful tips about Predictive Analytics!
About Thomas Haunschmid:Thomas Haunschmid lives and works in Lower Austria. After studying “IT Security” at the University of Applied Sciences, he worked in a leading position as IT project manager. Ten years later, he moved to a globally active company in the construction industry.
As “Business Manager E-Commerce” he is responsible for the roll-outs of the online shop in the country organisations and develops market entry strategies and marketing measures for the successful positioning of the online shop together with the regional marketing managers. While working, he completed a Master’s degree in “Product Marketing and Innovation Management” at the Austrian Marketing University in Wieselburg (Lower Austria).
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