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Author: Sudipta Chakraborty

  • Integrating Agentic AI for Enterprises: Opportunities, Governance, and Ethical Alignment

    The development of artificial intelligence is now at a new level—one that will augment its role within enterprise strategy. Agentic AI is more than automation or data processing; it is a class of intelligent systems capable of autonomously developing goals, making decisions, and taking action.

    Organizational leaders must think strategically, be able to coordinate operational processes, and ensure governance and ethical alignment.

    From Reactive to Proactive Intelligence

    Traditional AI models have assisted many business functions by accelerating workflows, improving analytics, and enabling process automation; however, these are primarily reactive systems as they can only operate within prescribed definitions and when instructed by a human.

    The world of agentic AI takes us out of this predictable paradigm. Agentic AI is a new opportunity for a more proactive AI – one that is capable of acting without prompting, contextualizes actions, and learns from actions to modulate behavior in a real-time space.

    The move from AI as a supportive technology to AI as a decision-enhancing technology is a meaningful shift in thinking about decision-making. It will provide us with new opportunities in a business environment that is unpredictable.

    Business Opportunities: Strategic and Operational Value

    Integrating Agentic AI for business units provides various benefits:

    • Customer Experience: AI agents can drive customer service workflows, manage problem resolution, and escalate exceptions independently, which improves the response time and ultimately, customer satisfaction.
    • Operations: Adaptive systems can respond to supply chain planning disruptions, optimize inventories, and reroute logistics in real time, resulting in decreased downtime and cost.
    • Revenue Functions: Sales and marketing units can fundamentally leverage autonomous agents, allowing them to experiment, learn, and customize campaigns in a personalized way, utilizing live dynamic feedback.
    • Knowledge Management: AI can augment the ability to surface insights, draft reports, or provide insight into complicated decision-making, allowing executives and analysts to reduce their cognitive load.

    In summary, Agentic AI enables organizational agility at scale, which will be crucial and highly valued in increasingly volatile and uncertain markets.

    Governance and Oversight: The Risk of Autonomy is Structural

    The complexity in governance and accountability increases with AI, making autonomous decisions. Business leaders and practitioners must build frameworks to answer essential questions such as:

    • How do we validate the reasoning behind its autonomous actions?
    • Who will be responsible for the decisions taken by the autonomous AI agent?
    • What checks are in place to ensure that the agent’s work aligns with the organizational goals and compliance standards?

    Businesses need to think about building policies considering legal and data compliance to ensure proper audit trails are created for tracing the action taken by AI, and building accountability models that can guide these audit trails. Adding human intervention at various decision-making touchpoints will establish escalation paths and help prevent any risks.

    Ethical Alignment

    The ethical implications of Agentic AI impact trust, brand reputation, and sustainability.

    Reputational damage (choosing to ‘put out a fire’ kind of conduct) in terms of bias in training data, a lack of transparency into the logic of decision-making, and hidden behavioral drift can result in reputational damage, regulatory risk, and customer loss.

    Companies should simply weave ethical design principles into the AI lifecycle:

    • Consistent assessments to ensure fairness and reduce bias.
    • Reviewing the explainability of model output.
    • Inclusively using data sources and designing user experiences.

    Ethical alignment is not soft – it’s a strategic necessity within the current landscape and accompanying expectations from stakeholders for humans and machines to be held accountable.

    Lead with Purpose

    Agentic AI is more than an upgrade in technology – it’s a shift in how a business operates, produces, and serves each stakeholder in a manner we collectively recognize as “the place where the bottom line meets social conscience”. The most successful organizations won’t be the first to adopt the technology, but rather the organizations that are thoughtful when integrating the technology while also balancing opportunity, governance, and ethical stewardship.

    As we introduce Agentic AI into our organizations, we need to consider how the clarity of our vision and sense of responsibility matter; we’ve reached a time when AI doesn’t just help, it acts.

  • The Rise of Voice Search Marketing

    In this ever-evolving digital marketing era, it’s crucial to stay ahead of the curve for businesses that aim to capture the attention of their target audience. Voice Search Marketing is one trend that has been making waves and is set to reshape the landscape — the era of typing queries into search engines is gradually giving way to a more natural and conversational approach.

    The Voice Search Revolution

    Consumers are increasingly using voice search to streamline their online experiences. Voice-enabled devices like smart speakers, smart TVs, virtual assistants, and smartphones with voice recognition technology have become ubiquitous.

    Traditional SEO strategies evolve as users shift from typed searches to vocalized queries. Long-tail keywords are becoming more critical as people use natural language when speaking to voice-activated devices.

    Optimizing for Voice Search

    i) Conversational Content is Key:

    Crafting content in a conversational tone is crucial for voice search optimization. Users tend to phrase voice queries in a more natural and spoken manner, so businesses need to adapt their content accordingly.

    ii) Local SEO and Voice Search:

    Voice searches often have a local intent. Optimizing for local SEO is paramount, ensuring that businesses appear in relevant voice search results, especially for queries like “near me” or location-specific requests.

    Emerging Technologies

    i) AI and Natural Language Processing (NLP):

    Integrating AI and natural language processing (NLP) enhances the accuracy and understanding of voice search platforms. Businesses are leveraging these technologies to provide more personalized and relevant results.

    ii) Visual and Voice Integration:

    Voice search is not limited to verbal interactions. Visual and voice integration is gaining traction, allowing users to initiate searches through images and continue the interaction through voice commands.

    Adapting Analytics for Voice

    Traditional analytic tools may struggle to attribute voice searches accurately, leading to challenges in understanding which interactions originated from voice commands. This limitation can hinder marketers’ ability to evaluate the benefits of their voice search optimization efforts. Additionally, users often initiate a voice search on one device and continue the interaction on another. Traditional analytics may not be able to connect these multi-platform journeys, leading to fragmented data and incomplete user profiles.

    Investing in analytics tools designed for voice interactions can provide more accurate insights. These tools can track and attribute voice searches, offering a clearer picture of user behavior and the effectiveness of voice search optimization strategies. Also, integrating cross-device tracking capabilities will allow marketers to follow users seamlessly across different platforms. This holistic view of user journeys enables more accurate attribution and a better understanding of the overall customer experience.

    Privacy Concerns:

    As with any data collection, voice search analytics raise privacy concerns. Users may hesitate to interact in voice if they feel their privacy is compromised. Marketers should prioritize transparency in data collection by clearly communicating how voice data is used, stored, and protected. Adhering to privacy regulations and obtaining explicit user consent can build trust and encourage more users to embrace voice interactions. By addressing these challenges and implementing tailored solutions, businesses can unlock the full potential of voice search marketing and gain a competitive edge in the evolving digital landscape.

    The Future of Voice Search Marketing

    As we look to the future, it’s evident that voice search is not just a current trend but a transformative force in digital marketing. Businesses that embrace this shift early on by optimizing their content for natural language and staying abreast of emerging technologies will have an advantage in being at the forefront of connecting with their target audience more naturally in 2024 and beyond.

  • Evolution of B2B Marketing Strategies

    Marketing strategies are ever-evolving, year after year, with 2019 being no different. Trends like live videos and video ads will continue to grow strong because of the instant visual appeal to the audience and with more than 80% of the internet users who indulge in watching these videos. Similarly, chatbots continue to trend this year by becoming widespread and pretty ‘normal’ for brands. The novelty factor has reduced, and they have become quite common.

    Here are some of the B2B strategies that aren’t new but continue to stay in the market:

    Longtail SEO: In the B2B space, the only way to compete with the big players with deep pockets is not to outspend them but to outsmart them. Smaller players should take advantage of the longtail keywords in their industry that have lower search volumes but more qualified searchers. Fewer websites compete for longtail SEO keywords. Hence, it’s comparatively easier to rank for them.

    Longform Content: We all know that the attention span of the consumer is very short. However, for B2B marketers, long-form content may just turn out to be more beneficial this year. The reason is that Google has started giving more weight to content that has authoritative information. It’s not just about keywords anymore.

    Also, from a lead-generation point of view, the prospects who dig deeper during the Awareness stage, even if just a small number, are the most profitable leads to take to the consideration stage.

    It’s clear that solid, detailed and in-depth information for the right leads at the right time improves the chances that the prospect will engage further and consider the brand.

    Micro-influencers: We all know that having big industry influencers advocate for our brands can ensure a large exposure based on their social media reach and engagement. This, of course, would require you to spend a pretty penny. On the other hand, we have “micro-influencers” who are smaller players in the industry but may have a more engaging follower list.

    The number of followers and, hence the social media reach, maybe smaller for the “micro-influencers”, but the engagement with the followers could be so much more powerful. It’s a new approach to not burn a hole in your pocket, but still, be able to reach out to your audiences effectively through an influencer. It’s just the right amount of smartly targeted PR within an optimal budget.

    Account-based marketing (ABM): ABM is a B2B strategy that focuses on sales and marketing resources on target accounts within a specific market. It’s a strategy that aligns sales and marketing efforts and takes advantage of available data, analytics, and technology.

    Though ABM has been growing through the years, personalizing the customer experience has started to catch on even faster than ever. With the help of CRM, marketing automation tools and digital marketing, marketers need to invest in a well chalked-out strategy that is going to support multimedia, multi-channel and multi-device targeting.

    With the growing competition, B2B marketers with limited budgets need to get smarter and need to build strategies based on these old but evolving trends that are here to stay.

  • 2018: Influencer Marketing for B2B

    Influencer Marketing picked up a lot of pace in 2017 and has stayed strong throughout 2018; a trend that is here to stay. In simple terms, Influencer Marketing is having someone advocate marketer’s story for them, like a blogger reviewing their product or someone on twitter sharing his or her opinion about the brand.

    Using Influencer Marketing for B2B companies for demand generation is a lot different than B2C due to the different mindsets among audiences. But is it really effective to use influencers in B2B marketing as well?

    Well, there are a lot of good reasons to invest in influencers and here are some:

    1. An influencer may have their own platforms and audiences on it that a B2B marketer can reach out to by connecting with the influencer.
    2. Influencers’ opinion is considered by their audiences as independent, unbiased and trustworthy.
    3. Often a popular influencer could help a marketer reach not only the digital world but also the traditional media, which is a win-win for the business.

    Over the years, the digitization of the media and marketing world has not only fueled the era of Influencers but also encouraged them to come up with their own set of platforms. This helps create more opportunities for the marketers to reach out to their audiences through the influencers.

    In 2018, B2B brands have increasingly used Influencers as their secret marketing technique. Consumers are more informed these days as they are very well connected and have more media inputs than ever. With the growing social media influence on consumers, Influencers play a crucial role for businesses to not only get their attention but to also, convert them into potential customers. According to a study conducted by NCS, Influencer Marketing can contribute to 11x higher return on investment than traditional marketing.

    There is no denying that Influencers could be very effective and work marketing miracles for B2B if done correctly, however, choosing the right influencer could be complex. The big question though is how can B2B marketers find the right influencers for their businesses.

    The most common mistake that’s made by the brands is going after popular influencers just because of the reach – the total number of people they can reach. Going after influencers that may have smaller but more targeted audience can help B2B business create a higher engagement. Larger reach doesn’t necessarily translate into better influence.

    However, it’s important for the marketer to clearly understand and define what they would want to achieve through influence marketing. If the aim is to just create awareness, going after the popular influencers is fine. But if the goal is to make the audience engage with the brand, then it’s important to identify the right influencer with the targeted audience. Influencers could be categorized as:

    1. Opinion Makers/Experts- Even though they may have a large number of followers as well, what makes them come out and be different is they are subject matter experts in their areas and simply exude the confidence while sharing their opinions which people trust. Trust can easily translate into buying decisions for their audiences.
    2. Advocates/Ambassadors- They are the ones who share their interests, opinion and the passion for a brand or product on a regular basis with their audiences on public platforms. They may not have a large audience but are very influential within their small groups of audiences and this translates to niche targeting for the brands. B2B companies may not consider these influencers as their best bet at influencer marketing, but it helps a great deal to connect with these advocates.

    An example of the above was the strategy of employee advocacy used by the company – Landis+Gyr, a global provider of energy management solutions across 5 continents and a pioneer in the energy industry. They shared content about their focus on customer needs, innovation, and core values through their employees’ social network. It worked really well for them as their campaigns accrued more than 1800 content shares and an estimated earned media value of over $10,800.

    IBM, a market leader in technology, on the other hand, promoted their IBM Watson platform by enabling a fashion designer to create the world’s first AI-inspired garment (Saree). This was unveiled at a awards ceremony for a large audience of women. It was very unique for IBM to market their AI platform using a celebrity fashion designer as an influencer.

    Cisco, a leader in networking and communication technology, has their community of IT advocates which they refer to as “Cisco Champions.” They have created a marketing program around them and use various incentives and awards to get these advocates to share their opinions and expertise on Cisco’s products on social media.

    It’s true that B2B influencer marketing is complex and choosing the right influencers could still be a work in progress for the industry. However, it might help a brand to have a good social media presence and keeping in touch with their customers. This may not only help to create opportunities for repeat business as a short-term impact but also create a way for successful influencer marketing in the long run.

    References:

    Nielsen Study Case Study

    Bringing Social Media to Life in the Energy Industry

  • Google AdWords & the Era of AI

    Digital advertising has changed tremendously in the past few years. The growth of the internet and advancements in technology have contributed to immense innovation in the world of online advertising. However, with growth comes challenges that are faced by today’s digital marketers.

    The rise of ad blockers, ad fraud, flawed data collection and analysis, complicated ad technology, and lack of training are a few roadblocks marketers face today. This prevents them from tapping the full potential of online advertising channels. The rise of Artificial Intelligence (AI), or machine learning, could be the answer to these challenges and has the potential to mold the entire marketing landscape as we know it.

    During Google’s I/O keynote in 2017, CEO Sundar Pichai shared Google’s shift in approach from a mobile first world to an AI first world. So, what does Google have in store for the digital marketers in 2018? As quoted by Google experts, “Machine learning can analyze countless signals in real time and reach consumers with more useful ads at the right moments.” Google AdWords can now help marketers gain more control over owning the right audience segment to target. People consume information, make online purchases, read and research on their mobile phones and tablets, and continue the same over their desktops and laptops. Mapping this journey across multiple devices used to be a difficult task, but it is now possible because of AI.

    Thanks to machine learning, here are some of the AdWords search features that will benefit marketers:

    1. Improved Smart Bidding – When a Google search is performed, AdWords optimizes bids considering multiple signals, which include device, location (physical and intent), day, time, and demographics. However, the improved smart bidding system now strategizes to “maximize conversions,” which doesn’t need a max CPA bid to work. It’s useful in determining the optimal CPA of a campaign and working backwards to meet the ROI targets.
    2. In-Market Search Audience – Previously, this feature was only available for display and YouTube advertising. Now that this feature is available for search, advertisers can target users or audiences who are actively looking for their products or services and can bid up on those searches where the user has relevant research history. The abilities of machine learning has made this possible by analyzing numerous search queries to figure out the intent trends of the users. Then, it shows the most relevant ads to the users which is closest to their interests.
    3. Life Event Search Audiences – Like the In-Market Search Audiences feature, Google also launched Life Event Targeting in 2017. This targeting option allows advertisers to target users around a few major life events including graduation, moving houses, and getting married. Google is planning on expanding this list in the future.
      Just like Search, Google also launched Smart Display Campaigns. Advertisers need to provide a target CPA, budget, and ad assets such as images and text headlines. The system learns on its own to optimize towards the goals.
    4. Data Driven Attribution – On the reporting front, Google AdWords uses machine learning to give credit to user touch-points for conversions or leads while finding a correlation between multiple unique ways in which a user’s path could lead to a conversion.
      AdWords AI is helping today’s advertisers save time daily when it comes to handling regular PPC campaign activities and management. This technology has free up time on account manager’s schedules to think of bigger things for their clients. However, advertisers still need to contribute their expertise, time, and effort to ensure the right inputs are fed into the systems for the machines to learn effectively.

    AI has begun to make its mark across the world. As technology continues to evolve, marketing technology will as well. Advertisers need to stay tuned, keep up, map the consumer response, and determine the right course of action for each new feature. After all, the machines learn from humans.

    Reference:

    https://adwords.googleblog.com/2017/05/ powering-ads-and-analytics-innovations.html