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受众细分:学习受众细分的基础知识,通过LIKE.TG改进您的电子邮件、短信和聊天机器人策略!

2024-03-13 09:42:56
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LIKE.TG 成立于2020年,总部位于马来西亚,是首家汇集全球互联网产品,提供一站式软件产品解决方案的综合性品牌。唯一官方网站:www.like.tg

受众细分是将整个受众分成具有共同特点的分段,如性别、年龄、地点、兴趣、行为等,以更好地定制营销优惠、广告和产品。

过去,设置细分是一项艰巨的任务,令营销人员头疼不已。今天,借助电子邮件营销社交媒体营销、消息营销、搜索引擎营销和其他数字营销渠道中简化的工具,即使是初级营销人员也能有效地对受众进行细分。

受众细分的3个原因

  1. 帮助您为受众提供个性化的服务
  2. 帮助您在竞争中脱颖而出
  3. 帮助您与受众建立有意义的关系

有几个原因您应该对受众进行细分,让我们一起来看看。细分:

  1. 帮助您为受众提供个性化的服务。如今,客户追求个性化体验,他们希望在合适的时间得到超级相关的优惠。这一切得益于社交网络和搜索引擎开始收集有关人们的行为和人口统计数据,以便品牌可以将人们分成不同的细分,并更精确地定制他们的信息。
  2. 帮助您在竞争中脱颖而出。激烈的在线营销竞争使得如今很难营销您的产品。然而,如果您在细分方面做得聪明,您可以比竞争对手更好地定制您的广告,培养并转化潜在客户。
  3. 帮助您与受众建立有意义的关系。为了满足现代客户的需求,品牌需要教育和娱乐他们。借助细分工具,公司可以制定有思想的内容营销战略,吸引每位客户。

现在让我们分析一下您可以对受众进行细分的方法。

受众细分的3个关键策略

  1. 人口统计细分
  2. 行为细分
  3. 根据购买者的旅程阶段进行细分

有三种主要的细分类型:人口统计、行为和购买者旅程细分。让我们对每个类型进行详细讨论。

人口统计细分

这种类型的细分帮助您根据典型的营销人口统计数据将受众分成不同的细分。让我们看一些最受欢迎的人口统计数据

  • 年龄。这是一个关键的细分变量,因为人们的喜好在他们的一生中不断变化。不同年龄段的人以特定的方式与品牌沟通,因此在您进行营销时需要进行研究并考虑这些差异。如果您经营服装业务,您需要为不同年龄段(儿童、青少年和成人)推出不同的系列。
  • 性别。每个性别都有特定的思考过程、需求和欲望。例如,男性和女性通常希望购买不同的身体护理产品。然而,您应该小心避免基于性别刻板印象的广告,因为这会冒犯部分潜在客户并使您的品牌看起来性别歧视。
  • 地点。这是一个重要的细分变量,因为人们使用不同的语言,有不同的文化、气候条件、时区等。除此之外,特定地区的企业有必要将其信息针对本地受众。没有必要将营销预算浪费在永远不会来到您店铺的人身上。
  • 收入。根据您的客户预计的工资,您可以为合适的人群定制不同级别的产品。例如,在汽车行业,向收入较低的人们广告销售头等运动车辆没有多大意义。在这种情况下,最好推广二手车或提供低利率的新车。而那些收入较高的人更有可能购买奢侈品牌。
  • 职业。一些利基产品是基于就业情况进行定制的:医疗设备、木工工具、健身器材、软件等。
  • 种族。了解相邻国家之间的文化差异和冲突非常重要。想想亚美尼亚和阿塞拜疆,或者西班牙和加泰罗尼亚危机。在与您的客户的国家进行沟通时,请注意关注他们国家的情况。此外,随着您的业务扩展到国际市场,进行研究也是必要的。
  • 家庭结构。想想超市中的“家庭装”产品。最好将这些产品定制给有三个或更多成员的家庭。有了关于家庭结构的数据,您可以快速确定这类产品的目标受众。

行为细分

行为细分基于用户的购物习惯和他们与您品牌的互动方式。让我们回顾一下根据行为对用户进行细分的最常见方法:

  • 购买行为。寻找阻止用户做决定的任何障碍。人们犹豫购买的原因有三个:他们在等待最佳优惠、他们在寻找社会证明,或者他们只是“四处看看”并不着急购买。利用购物节日来转化第一类人,从满意的客户那里收集反馈,对第三类人不要花费太多时间和精力,因为他们不太可能购买任何东西。
  • 好处。这是一种根据用户寻找的好处来划分客户的方式。您可以通过强调产品的最佳部分和好处来激励他们购买您的产品或服务。例如,口香糖可以使人们拥有洁净的牙齿、清新的口气、美味的味道,甚至具有抗压效果。找出驱使您的客户购买的好处,并强调它们。
  • 参与水平。一些用户偶尔与您的品牌联系,因此您可以对他们进行调查,了解他们是否认为您缺乏价值或动力。其他人经常使用您的服务,但没有充分利用其功能。分享如何使用视频,并突出对他们有用的所有功能。最后,将您的品牌整合到他们的生活中的人需要特殊的对待。您可以向他们提供奖励、忠诚计划,并在生日和周年纪念日上致以问候。
  • 特殊场合。此细分类型可帮助您在正确的时间传递信息。利用黑色星期五、网购星期一、国家假期等活动,增加购物的动力。您可以通过收集来自订阅表单、潜在客户磁铁或调查问卷的数据来实施基于场合的细分。这些见解将有助于树立您的积极品牌形象。

根据购买者的旅程阶段进行细分

购买者的旅程分为三个阶段:意识、考虑和决策。在每个阶段,潜在客户需要不同类型的对待。

如果用户刚刚发现他们有一个问题,他们通常会使用谷歌寻找解决方案。因此,在这个阶段,最好有能够回答未来客户问题的有用内容。可以是一篇文章,介绍如何用不同的方式解决问题。

如果用户已经知道哪种产品可以解决他们的问题,他们将希望了解更多关于其特性的信息,并确定他们需要哪种特定的产品。展示“最佳工具”之类的评论是个好主意。

一旦他们确定自己需要什么,用户会开始寻找最优惠的价格。如果您的品牌在购物广告中可见,这是与竞争对手脱颖而出的好方法。

如果用户仍有疑虑,您可以根据他们的搜索查询和兴趣,在Facebook或Google上以精准的广告来培养他们。

其他类型的受众细分

以下是一些额外的细分类型,可以丰富您的策略:

  • 基于之前的互动进行细分。这种类型的细分允许您根据客户以前的行为来提供超级相关的内容和广告。
  • 根据设备类型进行细分。这样可以将优化的消息发送给使用智能手机、台式机或平板电脑的人。
  • 客户忠诚度。忠实的客户对任何企业来说都是最有利可图的客户,因为他们具有最高的生命周期价值。这些人已经有权利获得独家内容和优惠。此外,与获取新潜在客户相比,保留现有客户和培养他们的忠诚度更便宜。忠实的客户更有可能成为品牌倡导者,并在他们的社交圈中推广您的品牌。
  • 客户满意度。这种类型的细分基于客户的反馈。它有助于在用户不满意产品之前解决问题。另一方面,它使您能够加强与已经喜欢您品牌的用户的关系。

我们来将一些受众细分应用到不同的营销渠道上。

如何在在线营销中使用受众细分

即使是初级营销人员也可以利用这项技术来造福他们的业务。让我们尝试在每个主要的数字营销渠道上执行受众细分。

电子邮件营销

批量电子邮件营销服务(如LIKE.TG、MailChimp、ConstantContact等)允许您通过订阅表单、调查、反馈和电子邮件分析来收集有关订阅者的数据

您通过订阅表单收集的每个订阅者都会为您带来未来细分的数据。您在订阅期间要求订阅者填写的字段越多,您将收到的信息就越多。然而,要求太多细节是不明智的,因为人们没有太多时间,也不太了解您,无法分享太多数据

这是使用LIKE.TG的电子邮件列表的样子。每列代表您可以用作细分变量的数据。它可以是订阅日期、用户评级、性别、位置等。在向受众发送电子邮件营销活动后,您可以根据他们的行为(如多久人们打开您的电子邮件、点击链接的次数等)对其进行细分。

有了这些见解,您可以发送更贴切的优惠、制定您的内容策略、发送重新参与活动以保留订阅者,并清理您的邮件列表。

以下是基于模板的个性化电子邮件,根据不同位置的受众细分显示不同的内容。

短信营销

与电子邮件营销类似,您需要在发送短信营销活动之前让受众选择订阅。对于手机用户来说,由于品牌无法收集大量有关他们的数据,因此更难进行细分。然而,如果您收集了有关忠实客户的信息,短信营销对他们非常有效。它可以帮助公司增加销售额、交叉销售和促销折扣。

使用LIKE.TG,您可以像电子邮件活动一样选择细分变量。以下是多米诺邮件针对一段时间没有来餐厅的人的文本消息。

33_4.png

Facebook广告

Facebook广告技术使初级用户能够创建具有强大定向能力的广告,提高与Facebook页面的互动,吸引新用户到您的网站等。

Facebook收集用户数据并为您提供简化的细分工具,所以除了创建内容并使用广告功能增加它之外,您不需要做任何事情。

要在Facebook上对受众进行细分,您需要选择目标受众的性别、年龄、地点、兴趣和行为模式。您可以将受众缩小到旧金山的男性,他们对健美感兴趣,年龄在18到40岁之间。服务还估计了您可以触及的潜在受众,对于这个特定的例子而言,是21万人。

33_2.png

聊天机器人

聊天机器人可以帮助您将订阅者引导进入销售漏斗。在与机器人的对话过程中,用户选择不同的问题并以不同的方式回答。在这里,细分发挥作用——您可以根据用户与聊天机器人的互动将用户添加到不同的细分,并在私人消息中发送精确定位的优惠。

一个明智构建的聊天机器人可以确定您的潜在客户在销售漏斗中的位置、他们的兴趣水平、偏好以及年龄、性别、位置等人口统计数据。基于这些见解,您可以将受众划分为不同的细分,并将这些信息用于进一步的沟通和广告,与您的受众建立持久而富有成效的关系。

以下是一个旅行行业机器人的示例,它从开始就根据位置对受众进行细分,然后将用户引导到购票流程。

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让我们通过回顾一些提示来帮助您掌握受众细分。

受众细分成功的4个最佳实践

  1. 不要过度细分
  2. 设定明确的目标
  3. 测试和改进
  4. 在每个渠道上对受众进行细分

我们总结了一些最佳实践,这些实践将帮助您以正确的方式对受众进行细分。

  1. 不要过度细分。受众细分需要平衡。如果您将受众缩小得太多,只有少数人将满足您所有的细分标准,这将停止为您带来收益。最好的做法是首先为受众的每个成员提供令人兴奋和个性化的内容,并将细分作为支持性工具,帮助您实现这个目标。
  2. 设定明确的目标。与随意细分相比,最好根本不进行细分。要有效地对受众进行细分,您需要首先制定一个买家画像,创建您的买家旅程,并确定目标受众。只有这样,您才能为受众细分战略设定切实可行的目标。
  3. 测试和改进。监控您的受众如何变化,并根据这些变化调整您的策略。有时,您需要修订以前有效的细分,进行更多的研究和测试,以创建更好的细分。您的受众是一个不断变化的有机体,所以始终有改进的空间。
  4. 在每个渠道上对受众进行细分。每个数字营销渠道都有细分选项,利用这些选项是个好主意。这对您的业务可能是有益的。例如,您从Facebook获得的有关受众的见解可以帮助您更好地在其他渠道上细分您的受众,并节省资金和精力。

恭喜您,您已经学会了受众细分的基础知识,现在是时候开始使用LIKE.TG对您的电子邮件、聊天机器人和短信受众进行细分了!

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					10 Benefits That Explain the Importance of CRM in Banking
10 Benefits That Explain the Importance of CRM in Banking
The banking industry is undergoing a digital transformation, and customer relationship management (CRM) systems are at the forefront of this change. By providing a centralised platform for customer data, interactions, and analytics, CRMs empower banks to deliver personalised and efficient services, fostering customer loyalty and driving business growth. We’ll look closer at the significance of CRM in banking, exploring its numerous benefits, addressing challenges in adoption, and highlighting future trends and innovations. Additionally, we present a compelling case study showcasing a successful CRM implementation in the banking sector. 10 Questions to Ask When Choosing a CRM in Banking When selecting a top CRM platform for your banking institution, it is necessary to carefully evaluate potential solutions to ensure they align with your specific requirements and objectives. Here are 10 key questions to ask during the selection process: 1. Does the CRM integrate with your existing, financial and banking organisation and systems? A seamless integration between your CRM and existing banking systems is essential to avoid data silos and ensure a holistic view of customer interactions. Look for a CRM that can easily integrate with your core banking system, payment platforms, and other relevant applications. 2. Can the CRM provide a 360-degree view of your customers? A CRM should offer a unified platform that consolidates customer data from various touchpoints, including online banking, mobile banking, branches, and contact centres. This enables bank representatives to access a complete customer profile, including account information, transaction history, and past interactions, resulting in more personalised and efficient customer service. 3. Does the CRM offer robust reporting and analytics capabilities? Leverage the power of data by selecting a CRM that provides robust reporting and analytics capabilities. This will allow you to analyse customer behaviour, identify trends, and gain actionable insights into customer needs and preferences. Look for a CRM that offers customisable reports, dashboards, and data visualisation tools to empower your bank with data-driven decision-making. 4. Is the CRM user-friendly and easy to implement? A user-friendly interface is essential for ensuring that your bank’s employees can effectively utilise the CRM. Consider the technical expertise of your team and opt for a CRM with an intuitive design, clear navigation, and minimal training requirements. Additionally, evaluate the implementation process to ensure it can be completed within your desired timeframe and budget. What is a CRM in the Banking Industry? Customer relationship management (CRM) is a crucial technology for banks to optimise customer service, improve operational efficiency, and drive business growth. A CRM system acts as a centralised platform that empowers banks to manage customer interactions, track customer information, and analyse customer data. By leveraging CRM capabilities, banks can also gain deeper insights and a larger understanding of their customers’ needs, preferences, and behaviours, enabling them to deliver personalised and exceptional banking experiences. CRM in banking fosters stronger customer relationships by facilitating personalised interactions. With a CRM system, banks can capture and store customer data, including personal information, transaction history, and communication preferences. This data enables bank representatives to have informed conversations with customers, addressing their specific needs and providing tailored financial solutions. Personalised interactions enhance customer satisfaction, loyalty, and overall banking experience. CRM enhances operational efficiency and productivity within banks. By automating routine tasks such as data entry, customer service ticketing, and report generation, banking CRM software streamlines workflows and reduces manual labour. This automation allows bank employees to focus on higher-value activities, such as customer engagement and financial advisory services. Furthermore, CRM provides real-time access to customer information, enabling employees to quickly retrieve and update customer data, thereby enhancing operational efficiency. Additionally, CRM empowers banks to analyse customer data and derive valuable insights. With robust reporting and analytics capabilities, banks can identify customer segments, analyse customer behaviour, and measure campaign effectiveness. This data-driven approach enables banks to make informed decisions, optimise marketing strategies, and develop targeted products and services that cater to specific customer needs. CRM also plays a vital role in risk management and compliance within the banking industry. By integrating customer data with regulatory requirements, banks can effectively monitor transactions, detect suspicious activities, and mitigate fraud risks. This ensures compliance with industry regulations and safeguards customer information. In summary, CRM is a transformative technology that revolutionises banking operations. By fostering personalised customer experiences and interactions, enhancing operational efficiency, enabling data-driven decision-making, and ensuring risk management, CRM empowers banks to deliver superior customer service, drive business growth, and maintain a competitive edge. The 10 Business Benefits of Using a Banking CRM 1. Streamlined Customer Interactions: CRMs enable banks to centralise customer data, providing a holistic view of each customer’s interactions with the bank. This allows for streamlined and personalised customer service, improving customer satisfaction and reducing the time and effort required to resolve customer queries. 2. Enhanced Data Management and Analytics: CRMs provide powerful data management capabilities, enabling banks to collect, store, and analyse customer data from various sources. This data can be leveraged to gain valuable insights into customer behaviour, preferences, and buying patterns. Banks can then use these insights to optimise their products, services, and marketing strategies. 3. Increased Sales and Cross-Selling Opportunities: CRMs help banks identify cross-selling and upselling opportunities by analysing customer data and identifying customer needs and preferences. By leveraging this information, banks can proactively recommend relevant products and services, increasing sales and revenue. 4. Improved Customer Retention and Loyalty: CRMs help banks build stronger customer relationships by enabling personalised interactions and providing excellent customer service. By understanding customer needs and preferences, banks can proactively address issues and provide tailored solutions, fostering customer loyalty and reducing churn. 5. Enhanced Regulatory Compliance and Risk Management: CRMs assist banks in complying with industry regulations and managing risks effectively. By centralising customer data and tracking customer interactions, banks can easily generate reports and demonstrate compliance with regulatory requirements. CRMs and other banking software programs also help in identifying and managing potential risks associated with customer transactions. 6. Improved Operational Efficiency: CRMs streamline various banking processes, including customer onboarding, loan processing, and account management. By automating repetitive tasks and providing real-time access to customer information, CRMs help banks improve operational efficiency and reduce costs. 7. Increased Employee Productivity: CRMs provide banking employees with easy access to customer data and real-time updates, enabling them to handle customer inquiries more efficiently. This reduces the time spent on administrative tasks and allows employees to focus on providing exceptional customer service. 8. Improved Decision-Making: CRMs provide banks with data-driven insights into customer behaviour and market trends. This information supports informed decision-making, enabling banks to develop and implement effective strategies for customer acquisition, retention, and growth. 9. Enhanced Customer Experience: CRMs help banks deliver a superior customer experience by providing personalised interactions, proactive problem resolution, and quick response to customer inquiries. This results in increased customer satisfaction and positive brand perception.10. Increased Profitability: By leveraging the benefits of CRM systems, banks can optimise their operations, increase sales, and reduce costs, ultimately leading to increased profitability and long-term success for financial service customers. Case studies highlighting successful CRM implementations in banking Several financial institutions have successfully implemented CRM systems to enhance their operations and customer service. Here are a few notable case studies: DBS Bank: DBS Bank, a leading financial institution in Southeast Asia, implemented a CRM system to improve customer service and cross-selling opportunities. The system provided a 360-degree view of customers, enabling the bank to tailor products and services to individual needs. As a result, DBS Bank increased customer retention by 15% and cross-selling opportunities by 20%. HDFC Bank: India’s largest private sector bank, HDFC Bank, implemented a CRM system to improve customer service and operational efficiency. The system integrated various customer touch points, such as branches, ATMs, and online banking, providing a seamless experience for customers. HDFC Bank achieved a 20% reduction in operating costs and a 15% increase in customer satisfaction. JPMorgan Chase: JPMorgan Chase, one of the largest banks in the United States, implemented a CRM system to improve customer interactions and data management. The system provided a centralised platform to track customer interactions and data, allowing the bank to gain insights into customer behaviour and preferences. As a result, JPMorgan Chase increased customer interactions by 15% and improved data accuracy by 20%. Bank of America: Bank of America, the second-largest bank in the United States, implemented a CRM system to improve sales and cross-selling opportunities. The system provided sales teams with real-time customer data, across sales and marketing efforts enabling them to tailor their pitches and identify potential cross-selling opportunities. Bank of America achieved a 10% increase in sales and a 15% increase in cross-selling opportunities.These case studies demonstrate the tangible benefits of CRM in the banking industry. By implementing CRM systems, banks can improve customer retention, customer service, cross-selling opportunities, operating costs, and marketing campaigns. Overcoming challenges to CRM adoption in banking While CRM systems offer numerous benefits to banks, their adoption can be hindered by certain challenges. One of the primary obstacles is resistance from employees who may be reluctant to embrace new technology or fear job displacement. Overcoming this resistance requires effective change management strategies, such as involving employees in the selection and implementation process, providing all-encompassing training, and addressing their concerns. Another challenge is the lack of proper training and support for employees using the CRM system. Insufficient training can lead to low user adoption and suboptimal utilisation of the system’s features. To address this, banks should invest in robust training programs that equip employees with the knowledge and skills necessary to effectively use the CRM system. Training should cover not only the technical aspects of the system but also its benefits and how it aligns with the bank’s overall goals. Integration challenges can also hinder the successful adoption of CRM software in banking. Banks often have complex IT systems and integrating a new CRM system can be a complex and time-consuming process. To overcome these challenges, banks should carefully plan the integration process, ensuring compatibility between the CRM system and existing systems. This may involve working with the CRM vendor to ensure a smooth integration process and providing adequate technical support to address any issues that arise. Data security is a critical concern for banks, and the adoption of a CRM system must address potential security risks. Banks must ensure that the CRM system meets industry standards and regulations for data protection. This includes implementing robust security measures, such as encryption, access controls, and regular security audits, to safeguard sensitive customer information. Finally, the cost of implementing and maintaining a CRM system can be a challenge for banks. CRM systems require significant upfront investment in software, hardware, and training. Banks should carefully evaluate the costs and benefits of CRM adoption, ensuring that the potential returns justify the investment. Additionally, banks should consider the ongoing costs associated with maintaining and updating the CRM system, as well as the cost of providing ongoing training and support to users. Future trends and innovations in banking CRM Navigating Evolving Banking Trends and Innovations in CRM The banking industry stands at the precipice of transformative changes, driven by a surge of innovative technologies and evolving customer expectations. Open banking, artificial intelligence (AI), blockchain technology, the Internet of Things (IoT), and voice-activated interfaces are shaping the future of banking CRM. Open banking is revolutionising the financial sphere by enabling banks to securely share customer data with third-party providers, with the customer’s explicit consent. This fosters a broader financial ecosystem, offering customers access to a varied range of products and services, while fostering healthy competition and innovation within the banking sector. AI has become an indispensable tool for banking institutions, empowering them to deliver exceptional customer experiences. AI-driven chatbots and virtual assistants provide round-the-clock support, assisting customers with queries, processing transactions, and ensuring swift problem resolution. Additionally, AI plays a pivotal role in fraud detection and risk management, safeguarding customers’ financial well-being. Blockchain technology, with its decentralised and immutable nature, offers a secure platform for financial transactions. By maintaining an incorruptible ledger of records, blockchain ensures the integrity and transparency of financial data, building trust among customers and enhancing the overall banking experience. The Internet of Things (IoT) is transforming banking by connecting physical devices to the internet, enabling real-time data collection and exchange. IoT devices monitor customer behaviour, track equipment status, and manage inventory, empowering banks to optimise operations, reduce costs, and deliver personalised services. Voice-activated interfaces and chatbots are revolutionising customer interactions, providing convenient and intuitive access to banking services. Customers can utilise voice commands or text-based chat to manage accounts, make payments, and seek assistance, enhancing their overall banking experience. These transformative trends necessitate banks’ ability to adapt and innovate continuously. By embracing these technologies and aligning them with customer needs, banks can unlock new opportunities for growth, strengthen customer relationships, and remain at the forefront of the industry. How LIKE.TG Can Help LIKE.TG is a leading provider of CRM solutions that can help banks achieve the benefits of CRM. With LIKE.TG, banks can gain a complete view of their customers, track interactions, deliver personalised experiences, and more. LIKE.TG offers a comprehensive suite of CRM tools that can be customised to meet the specific needs of banks. These tools include customer relationship management (CRM), sales and marketing automation, customer service, and analytics. By leveraging LIKE.TG, banks can improve customer satisfaction, increase revenue, and reduce costs. For example, one bank that implemented LIKE.TG saw a 20% increase in customer satisfaction, a 15% increase in revenue, and a 10% decrease in costs. Here are some specific examples of how LIKE.TG can help banks: Gain a complete view of customers: LIKE.TG provides a single, unified platform that allows banks to track all customer interactions, from initial contact to ongoing support. This information can be used to create a complete picture of each customer, which can help banks deliver more personalised and relevant experiences. Track interactions: LIKE.TG allows banks to track all interactions with customers, including phone calls, emails, chat conversations, and social media posts. This information can be used to identify trends and patterns, which can help banks improve their customer service and sales efforts. Deliver personalised experiences: LIKE.TG allows banks to create personalised experiences for each customer. This can be done by using customer data to tailor marketing campaigns, product recommendations, and customer service interactions. Increase revenue: LIKE.TG can help banks increase revenue by providing tools to track sales opportunities, manage leads, and forecast revenue. This information can be used to make informed decisions about which products and services to offer, and how to best target customers. Reduce costs: LIKE.TG can help banks reduce costs by automating tasks, streamlining processes, and improving efficiency. This can free up resources that can be used to focus on other areas of the business. Overall, LIKE.TG is a powerful CRM solution that can help banks improve customer satisfaction, increase revenue, and reduce costs. By leveraging LIKE.TG, banks can gain a competitive advantage in the rapidly changing financial services industry.

					10 Ecommerce Trends That Will Influence Online Shopping in 2024
10 Ecommerce Trends That Will Influence Online Shopping in 2024
Some ecommerce trends and technologies pass in hype cycles, but others are so powerful they change the entire course of the market. After all the innovations and emerging technologies that cropped up in 2023, business leaders are assessing how to move forward and which new trends to implement.Here are some of the biggest trends that will affect your business over the coming year. What you’ll learn: Artificial intelligence is boosting efficiency Businesses are prioritising data management and harmonisation Conversational commerce is getting more human Headless commerce is helping businesses keep up Brands are going big with resale Social commerce is evolving Vibrant video content is boosting sales Loyalty programs are getting more personalised User-generated content is influencing ecommerce sales Subscriptions are adding value across a range of industries Ecommerce trends FAQ 1. Artificial intelligence is boosting efficiency There’s no doubt about it: Artificial intelligence (AI) is changing the ecommerce game. Commerce teams have been using the technology for years to automate and personalise product recommendations, chatbot activity, and more. But now, generative and predictive AI trained on large language models (LLM) offer even more opportunities to increase efficiency and scale personalisation. AI is more than an ecommerce trend — it can make your teams more productive and your customers more satisfied. Do you have a large product catalog that needs to be updated frequently? AI can write and categorise individual descriptions, cutting down hours of work to mere minutes. Do you need to optimise product detail pages? AI can help with SEO by automatically generating meta titles and meta descriptions for every product. Need to build a landing page for a new promotion? Generative page designers let users of all skill levels create and design web pages in seconds with simple, conversational building tools. All this innovation will make it easier to keep up with other trends, meet customers’ high expectations, and stay flexible — no matter what comes next. 2. Businesses are prioritising data management and harmonisation Data is your most valuable business asset. It’s how you understand your customers, make informed decisions, and gauge success. So it’s critical to make sure your data is in order. The challenge? Businesses collect a lot of it, but they don’t always know how to manage it. That’s where data management and harmonisation come in. They bring together data from multiple sources — think your customer relationship management (CRM) and order management systems — to provide a holistic view of all your business activities. With harmonised data, you can uncover insights and act on them much faster to increase customer satisfaction and revenue. Harmonised data also makes it possible to implement AI (including generative AI), automation, and machine learning to help you market, serve, and sell more efficiently. That’s why data management and harmonisation are top priorities among business leaders: 68% predict an increase in data management investments. 32% say a lack of a complete view and understanding of their data is a hurdle. 45% plan to prioritise gaining a more holistic view of their customers. For businesses looking to take advantage of all the new AI capabilities in ecommerce, data management should be priority number one. 3. Conversational commerce is getting more human Remember when chatbot experiences felt robotic and awkward? Those days are over. Thanks to generative AI and LLMs, conversational commerce is getting a glow-up. Interacting with chatbots for service inquiries, product questions, and more via messaging apps and websites feels much more human and personalised. Chatbots can now elevate online shopping with conversational AI and first-party data, mirroring the best in-store interactions across all digital channels. Natural language, image-based, and data-driven interactions can simplify product searches, provide personalised responses, and streamline purchases for a smooth experience across all your digital channels. As technology advances, this trend will gain more traction. Intelligent AI chatbots offer customers better self-service experiences and make shopping more enjoyable. This is critical since 68% of customers say they wouldn’t use a company’s chatbot again if they had a bad experience. 4. Headless commerce is helping businesses keep up Headless commerce continues to gain steam. With this modular architecture, ecommerce teams can deliver new experiences faster because they don’t have to wait in the developer queue to change back-end systems. Instead, employees can update online interfaces using APIs, experience managers, and user-friendly tools. According to business leaders and commerce teams already using headless: 76% say it offers more flexibility and customisation. 72% say it increases agility and lets teams make storefront changes faster. 66% say it improves integration between systems. Customers reap the benefits of headless commerce, too. Shoppers get fresh experiences more frequently across all devices and touchpoints. Even better? Headless results in richer personalisation, better omni-channel experiences, and peak performance for ecommerce websites. 5. Brands are going big with resale Over the past few years, consumers have shifted their mindset about resale items. Secondhand purchases that were once viewed as stigma are now seen as status. In fact, more than half of consumers (52%) have purchased an item secondhand in the last year, and the resale market is expected to reach $70 billion by 2027. Simply put: Resale presents a huge opportunity for your business. As the circular economy grows in popularity, brands everywhere are opening their own resale stores and encouraging consumers to turn in used items, from old jeans to designer handbags to kitchen appliances. To claim your piece of the pie, be strategic as you enter the market. This means implementing robust inventory and order management systems with real-time visibility and reverse logistics capabilities. 6. Social commerce is evolving There are almost 5 billion monthly active users on platforms like Instagram, Facebook, Snapchat, and TikTok. More than two-thirds (67%) of global shoppers have made a purchase through social media this year. Social commerce instantly connects you with a vast global audience and opens up new opportunities to boost product discovery, reach new markets, and build meaningful connections with your customers. But it’s not enough to just be present on social channels. You need to be an active participant and create engaging, authentic experiences for shoppers. Thanks to new social commerce tools — like generative AI for content creation and integrations with social platforms — the shopping experience is getting better, faster, and more engaging. This trend is blurring the lines between shopping and entertainment, and customer expectations are rising as a result. 7. Vibrant video content is boosting sales Now that shoppers have become accustomed to the vibrant, attention-grabbing video content on social platforms, they expect the same from your brand’s ecommerce site. Video can offer customers a deeper understanding of your products, such as how they’re used, and what they look like from different angles. And video content isn’t just useful for ads or for increasing product discovery. Brands are having major success using video at every stage of the customer journey: in pre-purchase consultations, on product detail pages, and in post-purchase emails. A large majority (89%) of consumers say watching a video has convinced them to buy a product or service. 8. Loyalty programs are getting more personalised It’s important to attract new customers, but it’s also critical to retain your existing ones. That means you need to find ways to increase loyalty and build brand love. More and more, customers are seeking out brand loyalty programs — but they want meaningful rewards and experiences. So, what’s the key to a successful loyalty program? In a word: personalisation. Customers don’t want to exchange their data for a clunky, impersonal experience where they have to jump through hoops to redeem points. They want straightforward, exclusive offers. Curated experiences. Relevant rewards. Six out of 10 consumers want discounts in return for joining a loyalty program, and about one-third of consumers say they find exclusive or early access to products valuable. The brands that win customer loyalty will be those that use data-driven insights to create a program that keeps customers continually engaged and satisfied. 9. User-generated content is influencing ecommerce sales User-generated content (UGC) adds credibility, authenticity‌, and social proof to a brand’s marketing efforts — and can significantly boost sales and brand loyalty. In fact, one study found that shoppers who interact with UGC experience a 102.4% increase in conversions. Most shoppers expect to see feedback and reviews before making a purchase, and UGC provides value by showcasing the experiences and opinions of real customers. UGC also breaks away from generic item descriptions and professional product photography. It can show how to style a piece of clothing, for example, or how an item will fit across a range of body types. User-generated videos go a step further, highlighting the functions and features of more complex products, like consumer electronics or even automobiles. UGC is also a cost-effective way to generate content for social commerce without relying on agencies or large teams. By sourcing posts from hashtags, tagging, or concentrated campaigns, brands can share real-time, authentic, and organic social posts to a wider audience. UGC can be used on product pages and in ads, as well. And you can incorporate it into product development processes to gather valuable input from customers at scale. 10. Subscriptions are adding value across a range of industries From streaming platforms to food, clothing, and pet supplies, subscriptions have become a popular business model across industries. In 2023, subscriptions generated over $38 billion in revenue, doubling over the past four years. That’s because subscriptions are a win-win for shoppers and businesses: They offer freedom of choice for customers while creating a continuous revenue stream for sellers. Consider consumer goods brand KIND Snacks. KIND implemented a subscription service to supplement its B2B sales, giving customers a direct line to exclusive offers and flavours. This created a consistent revenue stream for KIND and helped it build a new level of brand loyalty with its customers. The subscription also lets KIND collect first-party data, so it can test new products and spot new trends. Ecommerce trends FAQ How do I know if an ecommerce trend is right for my business? If you’re trying to decide whether to adopt a new trend, the first step is to conduct a cost/benefit analysis. As you do, remember to prioritise customer experience and satisfaction. Look at customer data to evaluate the potential impact of the trend on your business. How costly will it be to implement the trend, and what will the payoff be one, two, and five years into the future? Analyse the numbers to assess whether the trend aligns with your customers’ preferences and behaviours. You can also take a cue from your competitors and their adoption of specific trends. While you shouldn’t mimic everything they do, being aware of their experiences can provide valuable insights and help gauge the viability of a trend for your business. Ultimately, customer-centric decision-making should guide your evaluation. Is ecommerce still on the rise? In a word: yes. In fact, ecommerce is a top priority for businesses across industries, from healthcare to manufacturing. Customers expect increasingly sophisticated digital shopping experiences, and digital channels continue to be a preferred purchasing method. Ecommerce sales are expected to reach $8.1 trillion by 2026. As digital channels and new technologies evolve, so will customer behaviours and expectations. Where should I start if I want to implement AI? Generative AI is revolutionising ecommerce by enhancing customer experiences and increasing productivity, conversions, and customer loyalty. But to reap the benefits, it’s critical to keep a few things in mind. First is customer trust. A majority of customers (68%) say advances in AI make it more important for companies to be trustworthy. This means businesses implementing AI should focus on transparency. Tell customers how you will use their data to improve shopping experiences. Develop ethical standards around your use of AI, and discuss them openly. You’ll need to answer tough questions like: How do you ensure sensitive data is anonymised? How will you monitor accuracy and audit for bias, toxicity, or hallucinations? These should all be considerations as you choose AI partners and develop your code of conduct and governance principles. At a time when only 13% of customers fully trust companies to use AI ethically, this should be top of mind for businesses delving into the fast-evolving technology. How can commerce teams measure success after adopting a new trend? Before implementing a new experience or ecommerce trend, set key performance indicators (KPIs) and decide how you’ll track relevant ecommerce metrics. This helps you make informed decisions and monitor the various moving parts of your business. From understanding inventory needs to gaining insights into customer behaviour to increasing loyalty, you’ll be in a better position to plan for future growth. The choice of metrics will depend on the needs of your business, but it’s crucial to establish a strategy that outlines metrics, sets KPIs, and measures them regularly. Your business will be more agile and better able to adapt to new ecommerce trends and understand customer buying patterns. Ecommerce metrics and KPIs are valuable tools for building a successful future and will set the tone for future ecommerce growth.

					10 Effective Sales Coaching Tips That Work
10 Effective Sales Coaching Tips That Work
A good sales coach unlocks serious revenue potential. Effective coaching can increase sales performance by 8%, according to a study by research firm Gartner.Many sales managers find coaching difficult to master, however — especially in environments where reps are remote and managers are asked to do more with less time and fewer resources.Understanding the sales coaching process is crucial in maximising sales rep performance, empowering reps, and positively impacting the sales organisation through structured, data-driven strategies.If you’re not getting the support you need to effectively coach your sales team, don’t despair. These 10 sales coaching tips are easy to implement with many of the tools already at your disposal, and are effective for both in-person and remote teams.1. Focus on rep wellbeingOne in three salespeople say mental health in sales has declined over the last two years, according to a recent LIKE.TG survey. One of the biggest reasons is the shift to remote work environments, which pushed sales reps to change routines while still hitting quotas. Add in the isolation inherent in virtual selling and you have a formula for serious mental and emotional strain.You can alleviate this in a couple of ways. First, create boundaries for your team. Set clear work hours and urge reps not to schedule sales or internal calls outside of these hours. Also, be clear about when reps should be checking internal messages and when they can sign off.Lori Richardson, founder of sales training company Score More Sales, advises managers to address this head-on by asking reps about their wellbeing during weekly one-on-ones. “I like to ask open-ended questions about the past week,” she said. “Questions like, ‘How did it go?’ and ‘What was it like?’ are good first steps. Then, you need to listen.”When the rep is done sharing their reflection, Richardson suggests restating the main points to ensure you’re on the same page. If necessary, ask for clarity so you fully understand what’s affecting their state of mind. Also, she urges: Don’t judge. The level of comfort required for sharing in these scenarios can only exist if you don’t jump to judgement.2. Build trust with authentic storiesFor sales coaching to work, sales managers must earn reps’ trust. This allows the individual to be open about performance challenges. The best way to start is by sharing personal and professional stories.These anecdotes should be authentic, revealing fault and weakness as much as success. There are two goals here: support reps with relatable stories so they know they’re not struggling alone, and let them know there are ways to address and overcome challenges.For example, a seasoned manager might share details about their first failed sales call as a cautionary tale – highlighting poor preparation, aggressive posturing, and lack of empathy during the conversation. This would be followed by steps the manager took to fix these mistakes, like call rehearsing and early-stage research into the prospect’s background, business, position, and pain points.3. Record and review sales callsSales coaching sessions, where recording and reviewing sales calls are key components aimed at improving sales call techniques, have become essential in today’s sales environment. Once upon a time, sales reps learned by shadowing tenured salespeople. While this is still done, it’s inefficient – and often untenable for virtual sales teams.To give sales reps the guidance and coaching they need to improve sales calls, deploy an intuitive conversation recording and analysis tool like Einstein Conversation Insights (ECI). You can analyse sales call conversations, track keywords to identify market trends, and share successful calls to help coach existing reps and accelerate onboarding for new reps. Curate both “best of” and “what not to do” examples so reps have a sense of where the guide rails are.4. Encourage self-evaluationWhen doing post-call debriefs or skill assessments – or just coaching during one-on-ones – it’s critical to have the salesperson self-evaluate. As a sales manager, you may only be with the rep one or two days a month. Given this disconnect, the goal is to encourage the sales rep to evaluate their own performance and build self-improvement goals around these observations.There are two important components to this. First, avoid jumping directly into feedback during your interactions. Relax and take a step back; let the sales rep self-evaluate.Second, be ready to prompt your reps with open-ended questions to help guide their self-evaluation. Consider questions like:What were your big wins over the last week/quarter?What were your biggest challenges and where did they come from?How did you address obstacles to sales closings?What have you learned about both your wins and losses?What happened during recent calls that didn’t go as well as you’d like? What would you do differently next time?Reps who can assess what they do well and where they can improve ultimately become more self-aware. Self-awareness is the gateway to self-confidence, which can help lead to more consistent sales.5. Let your reps set their own goalsThis falls in line with self-evaluation. Effective sales coaches don’t set focus areas for their salespeople; they let reps set this for themselves. During your one-on-ones, see if there’s an important area each rep wants to focus on and go with their suggestion (recommending adjustments as needed to ensure their goals align with those of the company). This creates a stronger desire to improve as it’s the rep who is making the commitment. Less effective managers will pick improvement goals for their reps, then wonder why they don’t get buy-in.For instance, a rep who identifies a tendency to be overly chatty in sales calls might set a goal to listen more. (Nine out of 10 salespeople say listening is more important than talking in sales today, according to a recent LIKE.TG survey.) To help, they could record their calls and review the listen-to-talk ratio. Based on industry benchmarks, they could set a clear goal metric and timeline – a 60/40 listen-to-talk ratio in four weeks, for example.Richardson does have one note of caution, however. “Reps don’t have all the answers. Each seller has strengths and gaps,” she said. “A strong manager can identify those strengths and gaps, and help reps fill in the missing pieces.”6. Focus on one improvement at a timeFor sales coaching to be effective, work with the rep to improve one area at a time instead of multiple areas simultaneously. With the former, you see acute focus and measurable progress. With the latter, you end up with frustrated, stalled-out reps pulled in too many directions.Here’s an example: Let’s say your rep is struggling with sales call openings. They let their nerves get the best of them and fumble through rehearsed intros. Over the course of a year, encourage them to practice different kinds of openings with other reps. Review their calls and offer insight. Ask them to regularly assess their comfort level with call openings during one-on-ones. Over time, you will see their focus pay off.7. Ask each rep to create an action planOpen questioning during one-on-ones creates an environment where a sales rep can surface methods to achieve their goals. To make this concrete, have the sales rep write out a plan of action that incorporates these methods. This plan should outline achievable steps to a desired goal with a clearly defined timeline. Be sure you upload it to your CRM as an attachment or use a tool like Quip to create a collaborative document editable by both the manager and the rep. Have reps create the plan after early-quarter one-on-ones and check in monthly to gauge progress (more on that in the next step).Here’s what a basic action plan might look like:Main goal: Complete 10 sales calls during the last week of the quarterSteps:Week 1: Identify 20-25 prospectsWeek 2: Make qualifying callsWeek 3: Conduct needs analysis (discovery) calls, prune list, and schedule sales calls with top prospectsWeek 4: Lead sales calls and close dealsThe power of putting pen to paper here is twofold. First, it forces the sales rep to think through their plan of action. Second, it crystallises their thinking and cements their commitment to action.8. Hold your rep accountableAs businessman Louis Gerstner, Jr. wrote in “Who Says Elephants Can’t Dance?”, “people respect what you inspect.” The effective manager understands that once the plan of action is in place, their role as coach is to hold the sales rep accountable for following through on their commitments. To support them, a manager should ask questions during one-on-ones such as:What measurable progress have you made this week/quarter?What challenges are you facing?How do you plan to overcome these challenges?You can also review rep activity in your CRM. This is especially easy if you have a platform that combines automatic activity logging, easy pipeline inspection, and task lists with reminders. If you need to follow up, don’t schedule another meeting. Instead, send your rep a quick note via email or a messaging tool like Slack to level-set.9. Offer professional development opportunitiesAccording to a study by LinkedIn, 94% of employees would stay at a company longer if it invested in their career. When companies make an effort to feed their employees’ growth, it’s a win-win. Productivity increases and employees are engaged in their work.Book clubs, seminars, internal training sessions, and courses are all great development opportunities. If tuition reimbursement or sponsorship is possible, articulate this up front so reps know about all available options.Richardson adds podcasts to the list. “Get all of your salespeople together to talk about a podcast episode that ties into sales,” she said. “Take notes, pull key takeaways and action items, and share a meeting summary the next day with the group. I love that kind of peer engagement. It’s so much better than watching a dull training video.”10. Set up time to share failures — and celebrationsAs Forbes Council member and sales vet Adam Mendler wrote of sales teams, successful reps and executives prize learning from failure. But as Richardson points out, a lot of coaches rescue their reps before they can learn from mistakes: “Instead of letting them fail, they try to save an opportunity,” she said. “But that’s not scalable and doesn’t build confidence in the rep.”Instead, give your reps the freedom to make mistakes and offer them guidance to grow through their failures. Set up a safe space where reps can share their mistakes and learnings with the larger team — then encourage each rep to toss those mistakes on a metaphorical bonfire so they can move on.By embracing failure as a learning opportunity, you also minimise the likelihood of repeating the same mistakes. Encourage your reps to document the circumstances that led to a missed opportunity or lost deal. Review calls to pinpoint where conversations go awry. Study failure, and you might be surprised by the insights that emerge.Also — and equally as important — make space for celebrating big wins. This cements best practices and offers positive reinforcement, which motivates reps to work harder to hit (or exceed) quota.Next steps for your sales coaching programA successful sales coach plays a pivotal role in enhancing sales rep performance and elevating the entire sales organisation. Successful sales coaching requires daily interaction with your team, ongoing training, and regular feedback, which optimises sales processes to improve overall sales performance. As Lindsey Boggs, global director of sales development at Quantum Metric, noted, it also requires intentional focus and a strategic approach to empower the sales team, significantly impacting the sales organisation.“Remove noise from your calendar so you can focus your day on what’s going to move the needle the most — coaching,” she said. Once that’s prioritised, follow the best practices above to help improve your sales reps’ performance, focusing on individual rep development as a key aspect of sales coaching. Remember: coaching is the key to driving sales performance.Steven Rosen, founder of sales management training company STAR Results, contributed to this article.
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The Power of AI and How Microsoft’s Supercomputer is Paving the Way
The Power of AI and How Microsoft’s Supercomputer is Paving the Way
As an AI enthusiast, I have always been fascinated by the power of computers with AI. The ability of machines to learn, adapt and perform complex tasks has revolutionized many industries, from healthcare to finance, education, and entertainment. But what is the future of AI, and how will it impact our world? In this article, I will explore the history, current state, and potential applications of AI, with a focus on Microsoft’s supercomputer and its collaboration with the MET Office to build a new generation of weather forecasting models.Introduction to AI and SupercomputersArtificial intelligence (AI) is a branch of computer science that deals with the development of algorithms and systems that can perform tasks requiring human-like intelligence, such as perception, reasoning, learning, and decision making. AI has been around for decades, but recent advancements in machine learning, deep learning, and natural language processing have opened up new possibilities for automation, optimization, and innovation.A supercomputer is a type of computer that has many processors, memory, and storage resources, allowing it to perform complex calculations and data analysis tasks at a much higher speed and scale than regular computers. Supercomputers are used in various fields, such as science, engineering, finance, and defense, to simulate and model complex phenomena, solve optimization problems, and process large amounts of data.The History of Computers with AIThe history of AI can be traced back to the mid-20th century, when researchers started exploring the idea of creating machines that could reason and learn like humans. One of the first AI systems was the Logic Theorist, developed by Allen Newell and Herbert Simon in 1956, which could prove mathematical theorems using symbolic logic. Another milestone was the General Problem Solver, created by J. C. Shaw and Herbert Simon in 1957, which could solve various problems using heuristic search and rule-based reasoning.In the 1960s and 1970s, AI research focused on expert systems, which were designed to mimic the knowledge and reasoning of human experts in specific domains, such as medicine, law, and finance. One of the most famous expert systems was MYCIN, developed by Edward Shortliffe in 1974, which could diagnose bacterial infections and recommend treatments based on the patient’s symptoms and medical history.In the following decades, AI research shifted towards machine learning, which involves training algorithms on large datasets to recognize patterns, classify objects, and make predictions. This approach has led to breakthroughs in computer vision, natural language processing, and speech recognition, enabling machines to perform tasks that were once thought to be exclusively human.The Current State of AI and its Impact on SocietyToday, AI is everywhere, from voice assistants like Siri and Alexa to self-driving cars, personalized advertising, and fraud detection. AI is also transforming industries such as healthcare, where it is used to diagnose diseases, develop new drugs, and improve patient outcomes. In finance, AI is used for fraud detection, risk management, and algorithmic trading. In education, AI is used for personalized learning, adaptive assessment, and intelligent tutoring.However, AI is not without its challenges and limitations. One of the main challenges is the bias and discrimination that can be introduced by AI systems, which are trained on biased data and can perpetuate and amplify existing inequalities. Another challenge is the ethical and legal implications of AI, such as privacy, transparency, and accountability. As AI becomes more pervasive and powerful, it is important to ensure that it is developed and used in a responsible and ethical way.What is a Supercomputer and How does it Differ from a Regular Computer?A supercomputer is a specialized type of computer that is designed to perform large-scale computations and simulations, are typically used for scientific and engineering applications that require high performance and accuracy, such as climate modeling, astrophysics, and quantum mechanics. Supercomputers are also used for data-intensive tasks such as big data analytics, machine learning, and artificial intelligence.Supercomputers differ from regular computers in several ways. First, supercomputers have a much higher processing power, measured in floating-point operations per second (FLOPS), than regular computers.Supercomputers can perform billions or even trillions of calculations per second, whereas regular computers can only perform millions. Second, supercomputers have a larger memory and storage capacity, allowing them to process and store massive datasets. Third, supercomputers are often specialized for specific tasks, such as weather forecasting or genome sequencing, whereas regular computers are general-purpose and can perform various tasks.Microsoft’s Announcement to Build a Supercomputer for AIIn May 2020, Microsoft announced that it would build a new supercomputer for AI research, in collaboration with OpenAI, a leading AI research organization. The supercomputer, named Azure AI, is one of the top five most powerful supercomputers in the world, with a processing power of 285 petaflops, or 285 million billion calculations per second. Azure AI is designed to train and run large-scale AI models, such as natural language processing and computer vision, that require massive amounts of computing power and data.The collaboration between Microsoft and OpenAI is aimed at advancing AI research and development, and addressing some of the key challenges and opportunities of AI, such as data privacy, energy efficiency, and ethical considerations. Azure AI is also expected to support various applications of AI, such as autonomous vehicles, personalized medicine, and smart cities.The MET Office and Microsoft’s Collaboration to Build a Supercomputer for Weather ForecastingIn addition to the collaboration with OpenAI, Microsoft has also partnered with the MET Office, the UK’s national weather service, to build a new supercomputer for weather forecasting. The supercomputer, named the Cray XC50, is the most powerful weather and climate supercomputer in the world, with a processing power of 23.5 petaflops.The Cray XC50 is designed to run sophisticated weather and climate models, that can predict the weather up to 15 days in advance, as well as simulate the impacts of climate change on different regions and sectors.The collaboration between the MET Office and Microsoft is aimed at improving the accuracy and reliability of weather forecasts, and providing more detailed and timely information to the public and decision-makers.The Cray XC50 is also expected to support research on climate change and its impacts, and help develop strategies and policies to mitigate and adapt to climate change.The Potential Benefits and Applications of Microsoft’s SupercomputerThe potential benefits and applications of Microsoft’s supercomputer are numerous and diverse. Some of the key benefits include:Improved accuracy and speed of AI models, which can lead to better decision-making, efficiency, and innovation in various industries, such as healthcare, finance, and manufacturing.Faster and more detailed weather and climate forecasts, which can help mitigate the impacts of extreme weather events and support adaptation and resilience measures.Enhanced research and development in AI, climate science, and other fields, which can lead to new discoveries, technologies, and solutions to global challenges.Some of the key applications of Microsoft’s supercomputer include:Natural language processing and speech recognition, for applications such as chatbots, voice assistants, and language translation.Computer vision and image recognition, for applications such as autonomous vehicles, facial recognition, and quality control.Climate modeling and simulation, for applications such as climate prediction, risk assessment, and policy evaluation.Drug discovery and personalized medicine, for applications such as drug design, clinical trials, and precision medicine.The Ethical Implications of AI and SupercomputersAs AI and supercomputers become more powerful and pervasive, it is important to consider their ethical and societal implications. Some of the key ethical issues include:Bias and discrimination, which can be introduced by AI systems that are trained on biased data and can perpetuate and amplify existing inequalities.Privacy and security, which can be compromised by AI systems that collect, process, and store personal data without consent or protection.Transparency and accountability, which can be challenging in AI systems that are opaque, complex, and difficult to audit or explain.Employment and labor impacts, which can be significant in industries that are automated or augmented by AI, and can lead to job displacement, skill gaps, and income inequality.To address these ethical issues, it is important to develop and implement ethical frameworks, guidelines, and standards for AI and supercomputers, that take into account the diverse perspectives, values, and interests of stakeholders, such as users, developers, regulators, and civil society.The Future of AI and SupercomputersThe future of AI and supercomputers is both exciting and challenging. On the one hand, AI and supercomputers have the potential to transform many aspects of our lives, from healthcare to climate change, and enable new forms of creativity, productivity, and well-being. On the other hand, AI and supercomputers also pose significant risks and uncertainties, such as job displacement, inequality, and unintended consequences.To realize the full potential of AI and supercomputers, it is important to pursue a human-centered and responsible approach, that values human dignity, rights, and welfare, and addresses the ethical, legal, and social implications of AI and supercomputers. This approach requires collaboration and engagement among diverse stakeholders, such as governments, industry, academia, and civil society, and a commitment to transparency, accountability, and participation.Conclusion and Final ThoughtsIn conclusion, AI and supercomputers are powerful tools that can help us tackle some of the most pressing challenges of our time, from climate change to healthcare. Microsoft’s supercomputer, in collaboration with OpenAI and the MET Office, represents a significant step forward in AI research and development, and has the potential to unlock new opportunities and benefits for society.However, it is important to recognize that AI and supercomputers also present significant ethical and societal challenges, that require careful consideration and action. By taking a human-centered and responsible approach to AI and supercomputers, we can harness their power for the greater good, and build a more inclusive, sustainable, and prosperous future.REMEMBER !!!You can downloadour available appsfor translating and learning languages correctly available for free on googleplay and applestores.Do not hesitate to visit ourLIKE.TG websiteand contact us with any questions or problems you may have, and of course, take a look at any ofour blog articles.
Artificial Intelligence Demystified: What It Is and How It Works
Artificial Intelligence Demystified
What It Is and How It Works
As a technology enthusiast, I have always been fascinated by artificial intelligence (AI). The idea of machines being able to think and learn like humans is both exciting and intimidating. In this article, I will attempt to demystify AI by explaining what it is, how it works, and the impact it has on society.Introduction to Artificial IntelligenceArtificial Intelligence, or AI, refers to the ability of machines to perform tasks that would normally require human intelligence, such as learning, perception, and decision-making. AI systems are designed to analyze vast amounts of data, find patterns, and make predictions. AI is a rapidly growing field, with new breakthroughs and innovations being made every day.What is Artificial Intelligence or AI? Understanding the BasicsAt its core, AI is a computer system that can perform tasks that would normally require human intelligence. These tasks can range from simple tasks like recognizing speech or images, to more complex tasks like playing chess or driving a car. AI systems are designed to learn from data, and can improve their performance over time.There are two main types of AI : narrow AI and general AI. Narrow AI, also known as weak AI, is designed to perform a specific task, such as recognizing faces or playing a game.General AI, also known as strong AI, is designed to perform any intellectual task that a human can do. However, we are still far from achieving true general AI.Evolution of AI TechnologyAI has been around for several decades, but it has only been in recent years that we have seen significant advancements in the technology. The development of neural networks and deep learning algorithms has allowed AI systems to analyze vast amounts of data and find patterns that were previously impossible to detect.AI technology has also become more accessible in recent years, with the development of open-source libraries and platforms. This has allowed developers to create AI systems without having to start from scratch, and has led to a proliferation of AI applications in various industries.Types of AI SystemsThere are several types of AI systems, each with its own strengths and weaknesses. Some of the most common types of AI systems include:Rule-based systems: These are systems that use a set of predefined rules to make decisions. For example, a rule-based system might be used to diagnose a medical condition based on a set of symptoms.Neural networks: These are systems that are designed to mimic the structure and function of the human brain. Neural networks are often used for image and speech recognition.Deep learning systems: These are neural networks that are designed to analyze vast amounts of data and find patterns. Deep learning systems are often used for natural language processing and predictive analytics.Expert systems: These are systems that are designed to replicate the decision-making processes of human experts. Expert systems are often used in fields like medicine and law.Applications of AI in Various FieldsAI has numerous applications in various fields, from healthcare to finance to transportation. Some of the most common applications of AI include:Healthcare: AI is being used to diagnose medical conditions, develop personalized treatment plans, and analyze medical images.Finance: AI is being used to detect fraud, make investment decisions, and analyze market trends.Transportation: AI is being used to develop self-driving cars, optimize traffic flow, and improve public transportation.Manufacturing: AI is being used to automate production processes, optimize supply chains, and improve product quality.How AI Works – Exploring the AI AlgorithmsAI systems use algorithms to analyze data and make decisions. These algorithms can be divided into two categories – supervised learning and unsupervised learning.Supervised learning algorithms are used when the system is given a set of labeled data, and is trained to recognize patterns in that data. For example, a supervised learning algorithm might be given a set of images of cats and dogs, and would be trained to recognize which images are of cats and which are of dogs.Unsupervised learning algorithms are used when the system is given a set of unlabeled data, and is tasked with finding patterns in that data. For example, an unsupervised learning algorithm might be given a set of customer transaction data, and would be tasked with finding patterns in that data that can be used to make business decisions.Future of Artificial Intelligence: Trends and PredictionsThe future of AI is both exciting and uncertain. On the one hand, AI has the potential to revolutionize numerous fields and improve our lives in countless ways. On the other hand, there are concerns about the impact of AI on jobs, privacy, and security.One of the biggest trends in AI is the development of explainable AI. Explainable AI refers to AI systems that are designed to provide clear explanations of their decisions and actions. This is important for ensuring that AI systems are transparent and accountable.Another trend in AI is the development of edge AI. Edge AI refers to AI systems that are designed to run on devices at the edge of the network, such as smartphones and IoT devices. This allows AI systems to be more responsive and efficient, and can improve the user experience.Advantages and Disadvantages of Artificial IntelligenceLike any technology, AI has its advantages and disadvantages. Some of the advantages of AI include:Increased efficiency and productivityImproved decision-makingEnhanced customer experienceImproved healthcare outcomesSome of the disadvantages of AI include:Job displacementSecurity and privacy concernsLack of transparency and accountabilityEthical concernsArtificial Intelligence and the Job MarketOne of the biggest concerns about AI is its impact on jobs. While AI has the potential to create new jobs and improve productivity, it also has the potential to displace workers in certain industries.According to a report by the World Economic Forum, AI is expected to displace 75 million jobs by 2022. However, the report also predicts that AI will create 133 million new jobs by 2022, resulting in a net gain of 58 million jobs.Artificial Intelligence Technology and Its Impact on SocietyAI technology has the potential to transform society in numerous ways, from improving healthcare outcomes to reducing traffic congestion to enhancing national security. However, there are also concerns about the impact of AI on society, particularly in the areas of privacy, security, and ethics.One of the biggest ethical concerns related to AI is bias. AI systems are only as unbiased as the data they are trained on, and if that data is biased, the AI system will be biased as well. This can lead to discrimination and other forms of unfairness.Future of AI TechnologyThe future of AI is difficult to predict, but it is likely that we will continue to see rapid advancements in the technology. Some of the areas where we can expect to see significant progress include:Natural language processingRoboticsExplainable AIEdge AIConclusionArtificial intelligence is a rapidly evolving field that has the potential to transform numerous industries and improve our lives in countless ways. However, there are also concerns about the impact of AI on jobs, privacy, and security. It is important to approach AI technology with caution and to consider the ethical implications of its use. As AI technology continues to evolve, we must be mindful of its potential benefits and drawbacks, and work to ensure that it is used in a responsible and ethical manner.To learn more about the latest developments in artificial intelligence technology, check out our blog.REMEMBER !!!You can downloadour available appsfor translating and learning languages correctly available for free on googleplay and applestores.Do not hesitate to visit ourLIKE.TG websiteand contact us with any questions or problems you may have, and of course, take a look at any ofour blog articles.
LIKE.TG API
LIKE.TG API
The most accurate translationLIKE.TG has its own translation API (with more than 125 languages, auto-detected language and language detected by geolocation) so you can get much more accurate results and improve communication.Break the language barriers with LIKE.TG !LIKE.TG Translate is available for both Android and iOS and is completely free.An indispensable tool if you like to travel, learn languages or converse with people who speak a different language than yours, perhaps … do you have someone special in mind?How does LIKE.TG API work?The app allows its users to positively rate the best translation results and after thousands of saved and thoroughly analyzed ratings, the translations have been adjusted to provide the most accurate results.In turn, the best translation engines such as Google, Microsoft, Deepl among others, to be even better.In addition, LIKE.TG’s API has its own database in which native human translators add advanced translations in different languages, therefore, the level of automatic translations is much higher than that of other common translation apps.In each translation, the intelligence of its own API analyzes the phrases in search of words which have definitions, synonyms, antonyms or examples and even verb conjugations in all tenses, they are called Smart Bubbles.In addition, within its server it has a large database to form “Books”, where you can find books in different languages, well organized by categories with different themes, with the invaluable help of expert translators.The automatic learning that makes up the server and its API constantly analyze the different languages to improve its translations and therefore, the more the application is used, the more data it receives and the more accurate and better its results are.Would you like to try it?REMEMBER !!!You can downloadour available appsfor translating and learning languages correctly available for free on googleplay and applestores.Do not hesitate to visit ourLIKE.TG websiteand contact us with any questions or problems you may have, and of course, take a look at any ofour blog articles.
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海外内容营销如何做?
海外内容营销如何做?
海外内容营销如何做? 什么是内容营销? 内容营销顾名思义就是公司或者品牌通过发布对其产品潜在受众有用的内容(例如博客、社媒帖子、短视频、白皮书等)来进行营销的手段。这些用于营销目的的内容通常在传递传达与产品或行业相关的专业内容时,也是为了找出潜在的受众,并向潜在受众展现品牌或者产品的价值和专业形象。 举个例子,比如著名的SEO工具Ahrefs,这家公司会定期地在Youtube上发布与SEO或者数字营销相关的教学内容,这就属于内容营销的典型,而这一系列行为也让他们赢得了很多公司产品的潜在销售对象(比如我)。 内容营销的重要性在哪? 如我们前面说到,内容营销是为了让你的潜在销售对象能够找到你,并且在你传递专业内容给他们的时候,让他们对你的品牌产生信任,展现你品牌的价值。 内容营销是一种已被证明有效的首选策略,这体现到数据上,就可以看到,拥有博客的企业比其他公司获得的销售线索多 67%。88% 的人相信品牌视频能够说服他们购买产品或服务。这么说吧,在21世纪进入到第二个十年后,内容营销已经成为每个企业必须采用的营销手段。 内容营销做的好的企业或者品牌,可以实现: 销量增加 节约成本 忠诚度更高的更好的客户 内容驱动的收入(即以内容为利润中心) 不同阶段的内容营销是如何运作的? 针对处于不同销售漏斗阶段的用户,企业是需要采取不同的内容营销策略,因为不同阶段的用户有着不同的内容需求。下面我将从漏斗顶部 - 觉察阶段、漏斗中部 - 考虑阶段、 漏斗底部 - 转化阶段,这三个阶段入手来讲述三个不同阶段的内容营销是如何运作的 漏斗顶部(TOFU) 在渠道的顶部,您希望通过您的内容建立知名度。 您的目标受众可能知道他们遇到了问题,但他们不确定如何解决。 在此阶段,您可以针对此类广泛存在问题做出专业性答复,也可以通过各种内容唤醒消费者对于这些问题痛点的觉察。 举个例子,比如我们现在职场人员经常会遇到的职业病如脖子酸疼、手腕疼痛等,对于这些问题,很多人在网络上会搜,脖子酸疼怎么恢复? 手腕疼痛怎么治疗?等一系列问题,这些属于漏斗顶部的受众会问的常见问题,此时他们只知道自己遇到了这个问题,但不清楚有哪些解决方案,假如此时你是一个生产各种按摩仪器的产商,那么你可以针对此类问题进行专业性答复,同时不失时机的在文章内推广自家的产品。 漏斗顶部有用的内容类型包括: 漏斗中部 (MOFU) 漏斗中部的潜在客户此时不仅意识到了问题,也知道该通过哪些方式解决问题,此时他们关注并在考虑你的产品,但是不太了解,处于查找信息并对比的阶段。这个阶段他们可能关注了你的社交媒体,也订阅了你的电子邮件推送。 此时,对于这些处于漏斗中部的客户而言,我们内容营销的侧重点不再是第一阶段当中的对那些广泛存在的常见问题进行解答,而是针对我们自身的产品或服务进行具体细节的讲解,突出优势,让他们能够在加深对产品的印象同时也能够提升产品或服务的信任。 优秀的漏斗中间内容类型包括: 漏斗底部 (BOFU) 进入到漏斗底部后,此时距离最终转化只差临门一脚了,此阶段客户已经对产品和服务有了充分的了解,但缺少立即下单的动力。 这个时候,我们在这一阶段的内容营销中要营造一种紧迫感, 如果是对价格要素考虑过多的用户,这种紧迫感可以通过限时促销的电子邮件或者社交媒体向用户进行传达,促使这类客户下单。 如果是对产品的需求实用性考虑过多的用户,我们可以通过一些营销内容,如加大宣传用户当前痛点亟待解决的方式来营造紧迫感。 此外,在一段阶段的内容营销中,要做好下单购买流程的优化,创造强大CTA标语。譬如页面中的购买链接要足够显眼且吸引人点击。 漏斗底部内容类型包括: 如何开始做内容营销? 内容营销可能会让人感到不知所措,但事实并非如此。 成功的内容营销活动应该是可管理且可持续的。 请按照以下步骤开始: 确定你的受众 在进行内容营销前,你需要确定你的受众是什么人群,处于什么样销售漏斗阶段,通过这样的形式进行分类从而能够针对不同的受众制定不同的营销内容方案。 确定正确的内容形式 对于不同的受众方案,我们需要不同的内容形式,确定好最合适的内容形式对于内容营销的效果至关重要。举个例子,对于那些已经确定要买电动车但是却不知道选哪个品牌的受众来说,此时此刻他们最需要的是一个关于不同电动车品牌的性能对比的内容,而不是告诉他电动车的优势。 你可以回答以下有关目标受众的问题,以帮助您确定适合他们的内容类型: 他们希望解决哪些问题? 你能针对他们的问题做出何种解答? 他们为什么选择你的产品或服务? 你需要从你制定的受众方案里的受众视角去入手,分析受众此时此刻受众最需要什么样形式的内容,你以何种方式呈现最好(文章、视频或是兼而有之?)总而言之,正确的格式与您的受众类型及其所处的销售阶段相对应。 确定分发渠道 写好对应的营销内容,这个时候就要确定分发渠道了,有些人可能会说,成年人不做选择,我无论什么样类型的营销内容直接一股脑全渠道分发,甭管啥社媒、博客、Youtube,通通给我铺上去。这个想法不能说不对,但是,你要考虑到一些内容并不适合多渠道分发。譬如说,你现在想要对那些处在漏斗底部只差一步就完成转化的人发布一个催促劝说+限时下单折扣的邮件营销内容,这个你能全域分发吗?不太可能吧! 对于通用性的内容营销,譬如一些常见性的指南、新闻等等你可以进行全域分发,但是针对某些特殊受众的,我建议还是挑选某个比较单一且私密的渠道,譬如针对性投流、电子邮件甚至是社交软件上的私聊都可以。 选择可持续的时间表 一旦您知道您的目标读者是谁以及销售周期每个阶段的最佳格式,就可以制定一个短期(3-6 个月)计划。 对于一些营销资源不是很丰富的小团队来说,一定不要设定过于浮夸的目标,从实际出发,根据自己人员和资金安排好规划,构思出在3-6个月的时间里想要做什么样的营销内容?通过哪些渠道进行分发? 这个时间安排可以先根据每年的节日和季节制定一个大体的框架,届时根据当时的热点新闻结合创作内容和营销方案。 制定指标并复盘效果 为你的内容营销制定一个可供衡量的指标并定期复盘核对每个内容营销方案的效果,这有利于你的方案迭代,这一步算是比较精细化的步骤,也许很多人刚开始进行内容营销时无法做到如此细致,但是大体的指标是一定要的,比如邮件打开率,网站流量、社媒互动率等。随着内容营销的逐步进行,可以逐步细化指标。 有效内容营销的特点 如果您的内容符合以下条件,您就可以为您的公司取得类似的成果: 1、内容以用需导向 任何企业或者任何个人想要获得成功,一定是要给大众创造价值的。内容营销不仅仅是分享产品的优点以吸引读者成为客户,那样就成了推销,任何人都反感。 重要的是要提供价值,譬如你的内容可以帮助到客户去更加有效地做某事,例如提高他们的业务利润或者改善某些环节的效率,那这就是价值。 无论情况如何,在内容营销的大多数情况下,都不应该提及过度地推销你自己的产品,除非你是在做自己的产品页,换而言之,内容营销中,也许我们的本质目的是销售,但是我们整体内容是围绕着客户的需求来撰写,而不是非常自我陶醉般地夸赞自己的产品,这会让客户非常下头。 比如护发品牌 Curlsmith 在博客文章帮助读者了解如何在高蛋白和高水分产品之间达到适当的平衡,它是首先教育读者,而直到最后才提到其产品。 2、针对性营销 提供价值并满足客户需求只是故事的一部分。 在每一篇内容中,您还应该针对客户的特定漏斗阶段进行营销。 一般来说,买家的旅程分为三个阶段:认知、考虑和决定。 在认知阶段,买家仍在研究他们的问题。 在考虑阶段,他们正在研究解决方案。 在决策阶段,他们将选择一家提供商。 如果您正在写“什么是 [X]?” 帖子,那么阅读该文章的人可能还没有准备好对其提供商做出决定。 他们仍处于意识阶段,正在完成研究,此时谁能提供解决他们疑惑的内容的人,毫无疑问会让他们提升好感。 相反,如果您正在编写某个产品测评的文章,那么访问该页面的读者已经研究了潜在的产品,并发现您是可能的提供商。 这意味着您应该在每个环节推销您的产品,重申您的价值主张并使自己在竞争中脱颖而出。 您不应该羞于承认产品最有价值的功能。 3、内容风格统一 无论您是在创建博客文章、网页还是电子书,您的访问者都应该能够在消费您的内容后立即知道您是谁。 你的品牌不应该听起来像是十个不同的人在为你写作,即使真实情况可能是如此。 就和我们有时候做个人IP需要有辨识度一样,品牌也是需要统一自己的内容风格,让用户形成鲜明印象,形成深刻记忆。 4、结合热点时事 这个说白了就是懂得蹭热点,蹭流量,在合适的时机发布正确的内容。即你的营销内容可以结合当前的时间和发生的热点事件进行创作,这样可以对你受众更加有吸引力。 举几个例子,假如你现在是某个酒类品牌的厂商,时至春节,此时我们是不是可以写一篇关于春节酒桌文化的文章来进行内容营销? 再举个例子,比如前段时间李佳琦不是因为眉笔事件而上了热搜,这时我们就可以结合这个热点事件进行相关的创作,至于具体创意就看你自己的发挥了!
TikTok如何养号?看完这篇养号运营教程你就懂
TikTok如何养号?看完这篇养号运营教程你就懂
TikTok养号运营教程 TikTok作为全球社交媒体界的一匹黑马,在诞生的这几年来斩获了全球十几亿的用户数量,在这种情况下对于外贸或者跨境电商行业的童鞋来说,TikTok现如今已经成为了线上推广营销的重要阵地,那么很多同学在注册完TikTok账号后却不知道如何去运营养号,很多时候在运营环境上或者作品内容采用了相对错误的方式去进行,就会导致TikTok账号运营的效果不太理想,比如观看量少,涨粉慢等,本次内容给予大家一些关于TikTok养号运营的注意事项,让大家能够初次接触TikTok时避免踏入误区! 如果还有童鞋不知道TikTok如何注册,推荐先阅读 TikTok账号如何注册?,先注册好TikTok账号! 养号的几大注意事项 1、个人注册资料要完善。 年龄建议选择18岁以上,个人简介尽量符合你后面TikTok内容的领域,同时绑定好其他的社交媒体账号(Instagram,Youtube等)。因为Tiktok是因受众兴趣导向进行算法分发的,简介和你做的内容要有高相关度,这样才可以获得更好的曝光效果。 2、要保持使用发布频率 。 前期发视频的频率适中,建议一周2-7条视频即可,保持一定的活跃度,让系统认为你是正常用户。避免一上来就大摇大摆地打营销广告,这样大概率没有好下场。建议起号时可以在前期先多刷刷视频、点赞、收藏和关注一些TikTok用户。 3、杜绝纯粹搬运抄袭。 不要搬运抖音Tiktok上已经有的作品,现在已经过了Tiktok纯粹搬运抄袭就可以获得好的结果的时候了,现在Tiktok查重机制非常严格,最好的方法是自己组织原创内容进行发布,当然也可以做半原创,只是下载素材需要是无水印的,同时剪辑的时候不要过度引用。 4、做好账号内容垂直度。 单个Tiktok账号的内容发布切忌雨露均沾,选定领域进行垂直创作才是最佳的方案,养号期间需要多去浏览这一块领域的内容,也多去搜索相关的关键词和内容,这不仅能让Tiktok推荐平台上更多的相同领域的优质内容给你借鉴,也可以给你账号留下标签,让后期TikTok大数据能把你的内容推给这领域的相关用户。 5、注意素材的版权 发布视频内容的时候,注意视频背景音乐素材,尽量选平台自有的,否则容易侵权,此外,可以使用当地流行的网络语言用词和缩写,更好地在TikTok进行互动,还有了解当地国家的一些风俗习惯,融入一些接地气的风士人情国家元素。 6、注重内容质量和用户互动。 TikTok注重国外用户的体验度,发布的TikTok视频尽量避免出现令观众不适的内容,同时也要避免在非中文地区使用中文。与此同时,发布视频后若有用户回复,也尽量抽出时间来去互动,这样可以更加好的去增加TikTok账号的活跃度和观众的好感度。 7、账号登陆设备和网络不要频繁变动 TikTok账号对于运营环境还是有一定要求的,建议选择一台固定的设备和搭配固定的网络进行作品发布,这样可以防范因设备或者网络因黑历史而导致账号被限流甚至关小黑屋的情况发生 TikTok养号标准流程示范 前三天 1、每天刷7-8个视频,给同类视频点赞,若属于同行业的垂直账户可以加关注。每个视频尽量看完 2、搜索关注同行业的优秀账号,观看他们的视频并点赞,如果真的觉得不错可以转发! 3、做好邮箱认证,以及社交媒体绑定,简介填写等完善资料的操作。 第四天开始 1、每天发布1-2个视频 (新账号前5-10个视频建议提前准备比较优质的精心打磨的视频内容) 2、查看发布视频的播放量,比较不同视频的播放量差异,做出调整。
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