Reimagine The Way your Business Operates
The new faces of Wealth Management
Wealth management has been one of the areas in fintech that has never really shined, apart from a few isolated cases like robo-advising and stock trading. Despite the vast potential it holds, the European wealth management sector is highly fragmented, and it is hard to build a one-fits-all solution (similarly to Vise or DriveWealth in the US). We are living in interesting times for new wealth management-related propositions. In particular, we are thinking of alternative asset classes and the expansion of ESG service providers (Environmental, Social and Governance). The dotted line is, once again, Covid and the effect it is having on the global monetary policies and individuals’ behaviour. We are still observing an an increasing demand for alternative portfolios and asset allocation in search of extra yield.
- Alternative asset classes
2021 is the year of crypto-related technologies (custody above others), fueled by the recent spike in BTC and ETH prices and driven by the entry of institutional market participants, with larger balance sheets (very different from the past retail-driven frenzy). Clear signals come from GS, BlackRock, Fidelity, Generali, Standard Chartered.A bunch of alternative asset classes (art, cars, reward points, etc) could also become investable and attract retail investors hungry for above-market performance. The US is already seeing a positive trend with companies like Bakkt and Rally (see a great post from John Street Capital). 2021 could see few European plays emerging in this space, like WiseAlpha(for fractional bond investing), Capdesk (a secondary market for private shares), TreasurySpring (offering Fixed-Term Funds to institutional investors).
- Environmental, Social and Governance
A “fight the climate change” action is being demanded to asset managers and financial players for a few years, spurred by the overwhelming evidence that climate is changing for the worst. Simultaneously, the money flooding into ‘ESG’ funds (Europe has recently surpassed the $1 trillion mark — an all-time high) has also highlighted the business opportunity for institutions that can respond. Weighing the ESG components has not historically been a critical input within the “get me more alpha” investment strategies. Things are now changing, driven by a growing demand for ESG-friendly assets and a higher regulatory demand/scrutiny. For us these are clear signals that there is a highway for companies like Matter, Util and Netpurpose (to name some), to support wealth and asset managers with new frameworks, data or compliance tools.
Blockchain IoT Market is Booming
It could be the biggest opportunity this year. The global blockchain IoT market is projected to garner growth at a CAGR of 73.5% during the estimate period 2021 to 2030 and to reach USD 31.2 billion by 2030.
Blockchain empowers the IoT devices to enhance security and bring transparency to the IoT ecosystem. It offers a scalable and decentralized environment to IoT devices, platforms and applications. It provides opportunities for businesses to run smart operations. It allows devices to send data to private blockchain ledgers for inclusion in shared transactions with tamper-resistant records. It enables business partners to access and supply IoT data without the need for central control and management.
- What are the Growth Factors
Factors such as growing adoption of Internet of Things (IoT), rising focus on operational efficiency, increasing requirement for IoT security, streamlining of business processes, better transparency offered by blockchain technology, increasing adoption of blockchain smart contracts are driving the growth of blockchain IoT market. Moreover, growing implementation of blockchain technology in the healthcare sector for reducing operational costs is driving the blockchain IoT market growth across the world. Additional features that are expected to fuel this business are integration of latest technologies and growing investment by governments. As millions of systems, services, and devices get linked, the consumers are receiving benefit from the enhanced lifestyle and businesses are becoming more competent as they minimalize their operational expenses and raise their asset application. The blockchain IoT market is anticipated be primarily driven by more ubiquitous and inexpensive sensors that translate the physical data to digital matter. The usage, application, and development of IoT will probably continue to grow with the launch of 5G (fifth-generation) cellular technologies and systems. The 5G technology allows bigger number of equipment’s to be connected concurrently to a network and interconnect with minimal adjournments, supporting not just consumer but commercial use of IoT systems and devices.
- Key Market Players and Strategies
The key companies functioning in the worldwide blockchain IoT market are The Linux Foundation, KrypC, Microsoft, Amazon, Ethereum Foundation, Cisco Systems, IoTEX, IBM, Intel, and R3 among others.
Impact of AI and Data Science on Digital Marketing
It is time to deploy AI & Machine Learning in Marketing Automation.
Are you constantly amazing by industry leaders who continue to push the envelope with hyper-personalized, relevant marketing? The secret lies in AI. Today’s customers have sky-high expectations for marketing. These expectations extend to a growing number of channels and devices that they access almost 24/7. What’s more, marketers are also expected to have a greater hand in crafting customer experiences (CX). So how are marketers supposed to deliver personalized messaging across a myriad of channels while remaining agile and responsive to customer preferences? The answer lies in AI marketing.
The multiplication of communication channels and the frequent interactions with users have made it harder to intercept the interests of each individual. As it is well known, without personalized experiences it is difficult to attract the attention of users.
If you mean to focus on users, you need data. In this context, a helping hand comes from Content Intelligence, a term indicating those strategies that apply Artificial Intelligence to content, in order to customize the visitor online experience. Content Intelligence works on two layers: the first one, through Speech-to-text, Image recognition, semantic analysis, automatically classifies content with tags. As a second step, Machine Learning algorithms track the content distributed on the front-end channels to collect data on users who use it.
The data set thus obtained constantly fuels your CRM, so you will have a tank of information on the user navigation path, updated in real time, that will make your Marketing Automation actions. We are already using this technology extensively in Marketing Automation (MA) applications. MA systems are programmed by people who teach them, through elementary logical mechanisms, to react to a given data input with a corresponding output or action (e.g. sending an email whenever a cart is left abandoned), and this will influence the performance of the whole platform. It is no longer people who set the rule establishing which product can be related to a certain type of person, but the platform itself, collecting as much data as possible from the users themselves, even through social media; ML can analyze it and define in self-learning the degree of affinity of a person with our e-commerce products, and adjust accordingly. When an abandoned cart occurs, the machine will decide on its own the most effective lead generation and nurturing strategy to use in order to keep the customer.
Thanks to data aggregation and self-learning, these new MA features can predict user behavior and quickly react with customized responses. What you get is predictive data: you can judge the percentage of affinity of a person with your products (for example 80%), and even with products found outside your sales platform. Tying MA to social activities and Machine Learning as we do means being able to intercept people desires in real time, and to establish the degree of interest of a cluster of people in a product or service. The combination of social media, data and Machine Learning can be beneficial for e-commerce. We tried it with Facebook and Twitter for the perception of sentiment towards the brand, its products and the audience “wishes”, and once all this data from social communications is processed by Machine Learning algorithms, you get recommendations that allow you to really personalize your marketing strategies.
We all want to feel treated in a unique way, so brands must gather differentiated information to ensure more effective communication. This is the case with advertising: if I receive offers I’m not interested in, they make me uncomfortable as they demonstrate that company does not know me, but if I get something relevant for me, I will pay more attention to it.
Having an automatic tool that recognizes affinity with the products enables a more targeted communication, in the same logic of inbound marketing. There are no alternatives: to provide a customized final action, data must be accompanied by a training of values. We brought this experience to both B2C and B2B. Take the case of a pharmaceutical company we are working with: when a customer is about to leave, by using the data collected the system can make a prediction on the best action to suggest.
Machine learning constantly learns from data, including historical data, so you can improve its intervention more and more. It is no longer a static analysis, but something more advanced.
The results are very convenient: greater loyalty, increased engagement and conversion rates.
L’Oréal shaping new trends in eCommerce
L’Oréal, the world leader in beauty, makeup, cosmetics, haircare is shaping new trends in eCommerce. At cosmetics giant L’Oréal, eCommerce has grown 65% during the pandemic to represent 25% of revenue. The shift to eCommerce is permanent, predicting that 50% of its sales will come from e-commerce by 2023. Further, e-commerce made up for more than 50% of its losses in brick-and-mortar during the pandemic and is expected to account for 50% of its sales by 2023.
L’Oréal leveraged the growth in online sales by spending more on platforms like Amazon that are performance-driven; in SEO to drive people to its own websites; and on ad formats like YouTube for Action. It’s also been spending more on virtual try-on technology, social commerce, and personalization. Its try-on technology ModiFace can now be found across 15 other sites and apps, including Amazon, YouTube, and Google Search. L’Oréal also invested this month in the social commerce platform Replika Software, which lets influencers, makeup artists and a hairstylists using its products to sell them directly to people online.
L’Oréal brands have all embraced the trend of social commerce and have experimented with different models: influencers, e-beauty advisors, as well as consumers and with very promising results.
L’Oréal wants to crack this new e-commerce channel that has a very strong potential in beauty and build a solid ecosystem of advocates and social sellers around the brand ecosystem.
The rise of e-commerce during the pandemic has also made marketing more conversational, with L’Oréal having a 40% rise in interactions with consumers across channels like Facebook Messenger and WeChat to pass 60 million interactions this year. That increase has given L’Oréal more data on which to base business decisions.
Employees 3x more likely to be engaged at work
Encourage the development and meaningful conversations. Continuous feedback through regular check-ins, whether it be one-on-one meetings, 360 feedback, or group supervision, are tools that foster communication and drive engagement in virtual environments.
More engaged employees directly transform into higher-performing employees. Investment in developmental and training opportunities can drive engagement. Having accessible content available on-demand across various platforms supports real-world, real-time development, nurtures engagement and drives performance in a virtual world.
A culture of honest feedback, and leaders who model what makes a great leader, generate workspaces where people feel heard, valued, and respected. Adopting a coaching approach involves having real conversations with frequent and honest feedback every week can result in employees being 2.7x more likely to be engaged at work.
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