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Month: May 2019

Enchantez vos audiences grâce au marketing en temps réel

Delight Your Audiences With Real-Time Marketing

If you have any familiarity with online marketing, you know that activating consumer data in real time is often talked about but isn’t easily achieved. This is because real-time marketing is dependent on a brand’s ability to:

  1. Identify the messaging and marketing channels that are driving the highest conversion rates
  2. Aggregate audience data, overlay it with insights, and create compelling segments
  3. Generate 360-degree customer views, which include online and offline behaviours across all devices

This all has to be done within a fraction of a second to truly engage users with the right content at the right time to influence their buying decisions.

Working behind the scenes are tag management solutions (TMS) and consent management platforms that must always be on, processing data in real time. For this reason, I have excluded them from this post, but it’s important to note that the TagCommander solution is viewed as the fastest TMS on the market. In fact, we recently landed a deal with the second-largest worldwide player in the online travel industry based on our solution’s speed.

The products from our suite of solutions that marketers are leveraging to facilitate real-time marketing are MixCommander, DataCommander, and recently released FuseCommander. They belong to the attribution, data activation, and identity reconciliation categories, respectively, and increase the effectiveness of your marketing campaigns by helping you better understand your consumers’ interests — and the mix of channels that are driving the highest conversion rates — so you can segment and present your audiences with effective messaging in real time.

From a marketing mix perspective, it’s critical for brands with large marketing budgets to know within the first few hours of launching if their campaigns are performing as expected. Marketers need timely data to identify what’s working (and what’s not) to make changes on the fly. In addition to providing real-time campaign performance data, MixCommander also offers cross-device reconciliation meaning it can identify a unique user who may have interacted with your online and offline ads using multiple devices. This provides better insight into the customer’s journey and the impact each channel and/or partner had. These real-time insights allow marketers to maximise their ROI by optimising spend by channel.

Understanding and exploiting the advertising mediums driving the most conversions is an important part of the equation. Equally, aggregating like audiences, including their interests and behaviours, and feeding these insights to your marketing orchestration tools for real-time activation is also critical. This can be achieved through DataCommander, which seamlessly collects user behaviours, standardises and creates relevant profiles, and pushes this data to your marketing orchestration platforms as segments for retargeting purposes.

Data entering the DataCommander platform is normalised and grouped, and subject to strict standards to avoid the old “garbage in, garbage out” adage, helping marketers minimise errors that could derail their personalisation efforts.

The last piece of the real-time data activation equation is creating 360-degree profiles providing marketers with visibility into a customer’s purchase history, browsing habits, mobile App usage, and prior campaign exposures across all devices and web browsers. This can be achieved with FuseCommander and opens the door for true one-to-one marketing experiences.

CommandersAct has an advantage over its competitors when it comes to activating data in real time because its R&D team began incorporating this into its product roadmaps years ago. CommandersAct’s products can be used together as a suite or on their own in conjunction with a brand’s existing Martech stack.

Michael Froment is the co-founder and CEO of Commanders Act.

Grâce à Commanders Act, Sorgenia profite des opportunités numériques pour personnaliser son offre et améliorer son service client

Thanks to Commanders Act, Sorgenia makes the most of digital technology to personalise the customer experience and improve customer support

The Italian energy supplier has achieved 15% more conversions by fully leveraging its data

Italy’s leading digital energy company

By making innovation its guiding principle, Sorgenia has become Italy’s leading digital energy company. The supplier, which provides gas and electricity to homes, entrepreneurs and small businesses, aims to offer customer service that is both friendly and sustainable.

Digital technology provides the answer

“The market is changing rapidly and will change even more so when it is fully liberalised. To respond quickly to these changes, we’ve decided to focus on digital technology to connect with our customers and offer them solutions that best meet their needs,” explains Paolo Rohr, Digital Director at Sorgenia.

The company has identified three main challenges:

Taking full advantage of the opportunities afforded by digital technology to help transition towards a free energy market;
Attract new clients;
Setting up a comprehensive support service that covers the entire customer journey.
Innovation and experimentation are Sorgenia’s two core principles and are clearly reflected in their technological choices. For Tag Management, Sorgenia chose to team up with Commanders Act.

A platform that adapts to the needs of the business

After scouting out various technology providers, Sorgenia chose Commanders Act for the flexibility of its products, comprising a complete suite of solutions perfectly adapted to the company’s needs. Two other factors played a key part in their decision: the comprehensive technical support available and the time saved by using a single platform. A single platform that allows:

Firstly, to create attribution models by analysing each customer’s journey, so that the company can know if customers need to contact customer service while also optimising all their processes.

And secondly, to provide a personalised browsing experience, allowing the the website to be adjusted depending on the type of visitor, customer or lead, and thus optimise the retargeting budget. And to also convert customers through the call centre. Thanks to Commanders Act’s solution, Sorgenia’s operators who contact a user following a support request can view a full data sheet with details of the customer’s profile. Naturally, this maximises the efficiency of the company’s support team and technicians.

A larger audience and a more targeted message with personalisation (10% more page views)

The content of Sorgenia’s website is personalised based on the user’s profile. If the user is a customer, the website proposes the purchase of a missing product or the Member Get Member programme to promote new supply contracts. On the other hand, if the user is a lead, the website aims to encourage the potential customer to visit the website again.

Another important aspect of the customer relationship is the daily promotions that the company offers through its agreements with online partners. The aim of these initiatives is to create a more detailed customer profile and provide unique communication.

Five months after starting this collaboration, the company is now almost completely independent in using the Commanders Act platform, and only needs technical support for complex issues. “We chose Commanders Act for the flexibility of its products and the availability of its staff. “What has been particularly great about this collaboration is the constructive relationship we have with Commanders Act – they are always proactive and ready to give us ideas and advice to constantly improve our service,” confirms Mr Rohr.

20-30% more traffic in the conversion funnel

Sorgenia has succeeded in increasing both the total volume of purchases and its conversion rates. Conversion rates have increased by 1%, leading to 15% growth in terms of total conversions. Combined with a more personalised service, this has led to 25% more traffic in the acquisition funnel. Looking at other metrics, the company has reduced its bounce rate by 1% and boosted page views by 10%. The number of browsing sessions has also increased, with each lasting 15% longer. In 2019, Sorgenia will continue to personalise its digital services, both for customers and leads: “We plan on integrating the data we have with other purchasing platforms and CRM activity. These are projects we are working hard to achieve, knowing we can count on our partnership with Commanders Act,” concludes Paolo Rohr.

Comprendre les données : que peut-on apprendre d'un arbre de décision ?  

Discovering Insights : What can be learned through a Prediction Tree?

Let’s take an example with this Prediction tree generated on an ecommerce website:

How to interpret it?

Red represents a strong probability of purchase (the darker the red, the higher the probability)
Blue represents a strong probability of no purchase (the darker the blue, the less chance a user will purchase)

The first point to the left represents 100% of the population, a first split occurs with the total_order_amount variable.

On one side, we have those whose total purchases (for their entire purchase history) amount to less than €25, and who are very unlikely to make a purchase (dark blue); on the other side, those whose total purchases amount to over €25 are slightly more likely to make a purchase (light blue)
Amongst the latter, those who were recently in the funnel are likely to make a purchase (light red circle) and out of these, those whose last visit was less than 28 days ago are even more likely to make a purchase (very dark red circle).

And for those whose 1st visit was over 28 days ago, we can see that those who recently viewed less than 22 pages are unlikely to buy, except when their total viewed pages is less than 55 and if they recently viewed over 4 pages.

However, those who have viewed a total of over 55 pages and who recently viewed less than 8 pages won’t make a purchase

Etc., etc. following the nodes

Lessons to take away

  • The most predictable variable is the total order amount, and it must be taken into account when you create your segments.
  • Recent presence in the buying tunnel drastically changes the probability (unsurprisingly, hence the importance of recovering abandoned baskets)
  • The number of page views is an indicator of purchase probability and depends on the date of the last visit (we can deduce that there is a sort of ratio that can determine if someone has a purchase intent based on the date of their first visit, total number of page views since and the number of recent page views).
    You must therefore create a segment for each red node on the far right of the screen to find all the visitors with an intent (or do further research into the ratio to create a new score variable to make this easier later on)
  • The other predictable variables to bear in mind are recent_view_product and recent_view_category. You can see that the higher they are, less chance there is of a purchase, no doubt because these are visitors who are just browsing without really knowing what they want, unlike those who look at few products and categories and who are more likely to buy quickly
Définir ce qui est le plus important : l'argent que vous avez ou l'argent que vous gagnez ?

What’s more important: The money you have or the money you earn?

Generally speaking, teams are rather excited when they start trying out machine learning, AI, predictive analytics and algorithms that have the potential to boost their work performance. However, the feedback in the press frequently overestimates the results achieved and gives the impression that soon everything will be done by a machine.

Unfortunately, marketers who have tried AI-powered marketing software have found themselves disappointed. Our team was very surprised to hear this, and so opened discussions with the first users of AI-powered solutions, mainly based in the US.

The first lesson to come out of this workshop was the feeling of a “Blackbox”. This term covers many different things, but the primary issue was that they wanted to know and understand how the machine worked. So, while the tool may have been doing its job well, it ignored the fact that marketing teams aren’t there to simply copy and paste the decision it has made; at least not at our current level of maturity. And that’s not without forgetting that the results weren’t even meeting the expectations of teams or management.

Nevertheless, this situation provided the perfect opportunity for us to rethink our R&D strategy. First of all, our team decided to help marketers understand the criteria that influence a conversion.By conversion, we mean any type of value that leads to events such as making a purchase, filling in a form, signing up to a newsletter, engaging on social media or viewing pages.

Machine learning is a vast topic, but we decided to apply quite a classic and popular approach called the Prediction Tree. It’s used in decision analysis to help decision makers identify a strategy that will most likely achieve a goal.

A decision tree is a flowchart-like structure in which each internal node represents a “test” on an attribute (e.g. whether a coin flip comes up heads or tails), each branch represents the outcome of the test, and each leaf node represents a class label (decision taken after computing all attributes). The paths from root to leaf represent classification rules.

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