As part of Solutions Review’s Premium Content Series—a collection of contributed columns written by industry experts in maturing software categories—Sajid Mohamedy, EVP of Growth and Delivery at Nisum, delves into the ways retailers can use artificial intelligence (AI) to keep up with big tech companies.

Amazon appears to be joining the AI race with a recent announcement stating they had developed a 10-week program catering to generative AI startups worldwide. This comes from the mounting pressure that numerous big tech companies are experiencing to elucidate their strategies for leveraging the swiftly progressing AI product market. 

Founders of these startups participating in Amazon’s program will gain valuable access to AI models, tools, and optimization for their machine learning stack. Additionally, they can expect to receive personalized guidance on go-to-market strategies. Following the public launch of ChatGPT in late November, big tech industry giants such as Google, Facebook, and Microsoft have also enthusiastically proclaimed their increasing emphasis on generative AI technology.  

Retailers worth their salt will note that AI has the potential to enhance the effectiveness and performance of sales operations by automating numerous repetitive tasks, enabling sales teams to allocate more time to interact with customers and potential buyers. This has a two-pronged effect—increasing customer engagement and reducing the cost of service. By leveraging AI coupled with organization-specific data and contextual information, businesses can obtain consumer insights at a much more detailed level.  

Given that 90 percent of commercial leaders are expected to utilize generative AI solutions regularly over the next two years. Let’s dive into how retailers can use the blueprint of Amazon—and other big tech players—to improve customer experience and unlock all kinds of other benefits. 

Real-Life Examples of How Retailers Can Utilize Generative AI 

Senior thought leaders in the retail industry have highlighted the potential of generative AI in enhancing product descriptions. The recent introduction of an AI tool by Shopify aims to assist vendors and merchants in improving their product descriptions. Retailers possessing extensive proprietary data enjoy a significant competitive edge over their counterparts. Consequently, this could motivate retailers to acquire additional first-party or zero-party data. The larger and higher quality data sets provide an expanded scope for creative endeavors. 

The application of generative AI in product recommendation is another possible area for retailers to engage in. Although retailers have yet to embrace generative AI for this purpose, many industries have already started experimenting with its recommendation capabilities. For example, Expedia has revealed its beta testing of ChatGPT within its mobile app, aiming to provide personalized travel recommendations and planning assistance to users. 

These are just a couple of current use cases, but experts anticipate the emergence of additional use cases for retailers regarding generative AI. Despite the challenging venture capital environment, funding for startups driving the growth of generative AI and other AI tools remains robust. VCs have steadily renewed their interest in generative AI, from $408 million in 2018 to a whopping $4.5 billion last year. 

Factors to Bear in Mind for Success 

By now, it is clear that retailers should prioritize and implement advanced sales technologies, establish hybrid teams, and embrace hyper-personalization. However, there are some key strategies to consider when implementing generative AI into operations. Maximizing the utilization of e-commerce platforms and third-party marketplaces through analytics and AI can significantly benefit. Based on successful companies’ practices, the following recommendations can be made: 

• Have a well-defined vision and strategy for integrating AI into operations. 
• Allocate more than 15 percent of digital budgets towards AI-related technologies. 
• Consider employing teams of data scientists to leverage algorithms for rapid pricing strategies and optimize marketing and sales efforts. 
• Focus on identifying and implementing practical use cases for AI. 
• Recognize the potential of generative AI to enhance overall operations.

By adopting these approaches, retailers can position themselves as trailblazers in their industry, harness AI to drive success, and compete with their big tech competitors.

Risk Mitigation 

Naturally, retailers need to be aware of the potential risks of generative AI. Firstly, there is a significant risk concerning the unintentional disclosure of confidential or proprietary information. As AI may use user conversations to enhance future results, there exists a possibility that confidential data might become accessible to the public or, worse yet, to competitors. Additionally, compliance with a comprehensive set of regulations outlined in the Security of Critical Infrastructure (SOCI) Act is another factor for retailers to consider. These measures are crucial to maintaining the confidentiality and security of sensitive information. 

Another critical concern regarding generative AI systems focuses on the issue of bias and fairness, particularly regarding data sets. This issue can pose significant reputational challenges for brands heavily dependent on this technology. For instance, if an image-generating tool is used with an advertising campaign containing inappropriate or offensive images that are subsequently shared globally, it could potentially damage the brand’s reputation. In these cases, attributing responsibility solely to the company’s AI system as a damage control measure might not be sufficient to appease consumer backlash. Consequently, addressing the biases and ensuring fairness within generative AI systems becomes crucial to safeguard the brand reputation and maintain positive consumer sentiment. 

Final Thoughts 

Generative AI—often accessible through cloud-based platforms and with future possibilities on the horizon—offers abundant opportunities for transformative breakthroughs for retailers. That being said, retail executives must maintain a vigilant understanding of the inherent risks present during this nascent phase of generative AI technology. By striking a balance between embracing the thrilling potential and exercising caution, retailers of all sizes and varying degrees of technological expertise can confidently navigate this evolving landscape.

The post Big Tech Companies Are Heavily Investing in AI: What Can Retailers Do to Keep Up? appeared first on Best Marketing Automation Software, Tools, Vendors & Solutions.

For each Solutions Review Finds post, our site editors shop for the best products, sift through the reviews, measure the top sellers, and report back with our picks. Here are the best cameras for video marketing. Solutions Review participates in affiliate programs and may make a small commission from products purchased through this resource.

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January 20, 2023Best Practices, Featured

Canon EOS M6 Mark II

SUMMARY: The Canon EOS M6 Mark II is a notable improvement for Canon’s mirrorless cameras. This model blends consistently high-quality optics with a compact design, a 32.5 Megapixel CMOS (APS-C) sensor, DIGIC 8 Image Processor, a high-resolution 3″ LCD tilting monitor, and 4K video recording. Videos shot with the camera will also use the camera’s face tracking, eye detection, and autofocus features so that users can track moving targets. 

PROS

• Accurate autofocus
• 4K video supports the use of the full width of the frame
• Reliable face and eye detection

CONS

• Lack of weather sealing
• Higher price
• No IBIS

OUR TAKE: Whiit on the pricier side, the Canon EOS M6 Mark II is regarded as one of Canon’s best mirrorless cameras. The full-width 4K video recording capabilities (which are not as common as you may think) and autofocusing features make this an excellent tool for marketers breaking into the video marketing field. If you’re looking for a cheaper alternative, the Canon EOS Rebel T7 is a popular option amongst consumers, especially those just getting started in the world of videography.

Nikon Z 30

SUMMARY: The Nikon Z 30 is the brand’s most compact, lightweight mirrorless video camera. The camera is equipped with fast, reliable autofocus, several AF Area Modes capable of adjusting to quick shifts in detail, eye-detection autofocus, image stabilization, a flip-out touchscreen selfie monitor, and more. And with its 3-inch LCD touchscreen, which can tilt up and down, users can easily shoot in high-quality resolution.

PROS

• Can record video for up to two hours straight
• Tilting LCD touchscreen
• Compatible with every NIKKOR Z lens

CONS

• No HDR recording
• Sometimes overheats
• Lack of EVF

OUR TAKE: The Nikon Z 30 may not be the camera for professional videographers who need all the newest and most dynamic features since it’s primarily geared toward content creators, vloggers, and streamers. However, it stands as a compelling option for marketers looking to get into video, as it’s an easy-to-use, reliably high-quality product that can scale with the user as their needs change. There’s even an affordable accessory package to help marketers get started!

Panasonic LUMIX G85

SUMMARY: The Panasonic LUMIX G85 is a DSLM camera equipped with the technologies and practical functionalities Panasonic users want and is paired with a compact body ideal for field use. The newly advanced 5-axis Dual I.S. (Image Stabilizer) suppresses blurring, so users can comfortably capture 4K video in 3840×2160 at 30p (60Hz) or 24p in MP4 formats. Other notable features include a 3″ touchscreen display with tilt and swivel capabilities, a weather-sealed body, dual image stabilization, and more.

PROS

• Sharp 4K (UHD) video
• Articulated LCD touchscreen
• Remote control capabilities via smartphone

CONS

• 4K videos are cropped by a factor of 1.10
• Underwhelming battery life
• Subpar low-light performance

OUR TAKE: This camera offers video marketers just about all the tools and features they need to shoot sharp, unique content for their audience. While it has its detractions, the 4K video—even with the 1.10 crop—and impressive image quality make this a compelling option in the mid-range pricing market. The camera’s remote control capabilities and overall durability are also big perks, as they make the Panasonic LUMIX G85 a unit you can take just about anywhere.

Sony a6400

SUMMARY: With the a6400, Sony has created a camera that strikes a successful balance between the needs of consumers and professional enthusiasts. The Sony a6400 is equipped with features like a 24.2 MP Exmor CMOS sensor, a 0.02-second autofocus speed, real-time autofocus and targeting functionalities empowered by machine learning technology, a 180-degree tiltable LCD touchscreen, and 4K video recording at 24, 25, or 30fps. The camera also supports Bluetooth, NFC, and Wi-Fi.

PROS

• 4K video without cropping or recording limitations
• Built-in pop-up flash, EVF, and hot shoe
• AI-enhanced tracking functionality

CONS

• Lack of in-body image stabilization (IBIS)
• No external battery charger
• The camera is not entirely weatherproof

OUR TAKE: The Sony a6400 is a great mid-market camera for marketers who want something more advanced than an entry-level product but without the cost of a professional-level unit. Its 4K video functionalities are reliably excellent. Unlike other cameras at this price point, you don’t have to worry about your footage being cropped or cut off after a certain amount of time has transpired—you’re free to film until the battery dies if you want. Some users may wish to upgrade the a6400 with a full-frame lens—the FE 24-105mm is a popular option—at some point, but the out-of-box capabilities should be more than enough for your video marketing needs.

Sony ZV-1

SUMMARY: Sony’s ZV-1 is a camera made with content creators and vloggers in mind. While it shares similar tech with Sony’s RX100 line, the ZV-1 branches out by focusing more on video-friendly capabilities and features. For example, ZV-1 includes image stabilization, face and eye detection, autofocus, and a metering system to maintain proper exposure in changing light conditions. Other features for videographers include a built-in microphone, 4K recording at 24 or 30fps, and a product showcase mode that automatically adjusts the focus when an object is centered.

PROS

• Sleek, compact form factor
• Terrific audio capture
• Impressive 4K video

CONS

• Disappointing battery life
• Narrow lens
• Touch functionalities are limited

OUR TAKE: If you’re looking for an accessible but reliable camera, the Sony ZV-1 is a fantastic option. It’s best suited for smaller marketing teams, especially ones focusing on more compact videos. The compact design, vlogger-friendly features, and reliable audio and video will quickly meet the needs of marketing video content. If you plan on taking the camera on the go, you will probably want to look into an accessory kit that includes a selfie stick or tripod, which will help compensate for the narrower lens.

NOW READ: The Best Video Marketing Courses Worth Taking

The post The 6 Best Cameras for Video Marketing to Consider Using appeared first on Best Marketing Automation Software, Tools, Vendors & Solutions.

As part of Solutions Review’s Premium Content Series—a collection of contributed columns written by industry experts in maturing software categories—Nishant Patel, founder and CTO of Contentstack, explains how composable architecture can minimize risks in a company’s martech stack.

Every IT leader wants to reduce risk while maximizing efficiency and quality. Gartner found that CIOs are searching for ways to accomplish this with their digital investments. However, while monolithic enterprise suites have become commonplace, they aren’t the best option for many companies’ needs—especially for CIOs pressured to accelerate time to value for investments.

The way a typical marketing stack is built increases risk, limits the experiences marketing can build and creates headaches for IT teams. Today, more marketing and IT leaders are choosing composable architectures. When you dive into the details, the reasons are clear.

The Basics of Composable Architecture

Conventional enterprise suites are built so that their components all work together, but they often don’t connect well to other platforms and apps. That’s fine if you are using them mostly by themselves. But today’s enterprises often need to patch different vendors’ products and technologies together, burdening IT with custom coding or some other method that presents a high risk of breaking.

Composable architecture trades the behemoth of a traditional suite for more of a plug-and-play model, where each part can be added, removed, or swapped like Legos. This flexibility allows you to pick and choose what tools to use. You can select the best ones for your use case and fit them together with minimal IT overhead. Integration, scaling, upgrading, and development all become more manageable with composable stacks, allowing you to increase your agility while reducing the workload of your IT department.

Composable Architecture Reduces Traditional Infrastructure Risks

Think about how much the digital world has changed in the last few years. Even new tools from only a few years ago can be old and outdated—relegated to “legacy” status. Your tools need to evolve to match your needs to keep up with the competition and get ahead.

When IT connects a monolithic system to other services, the solution tends to be fragile in a few ways. Updates to the applications can break the functionality. Edge cases that IT didn’t anticipate can fall through the cracks. And perhaps more importantly, these ad hoc solutions depend on your IT department’s ability to maintain them. That can put a significant strain on your engineers. Even when you have careful documentation of the solution, losing key talent to retirement or another company risks losing maintenance knowledge.

The composable architecture eliminates these risks. The components are designed to work together, even when dealing with different vendors, so IT doesn’t have extra work. This segmented approach also means that the failure of one component does not bring down the entire system. Unlike a monolithic suite, where a crash in one piece might cause the whole system to break, composable architecture is more resilient. And a more stable architecture frees your marketing team to focus less on maintenance and more on creativity.

Composable Architecture Maximizes Creativity

Salesforce found that 84 percent of customers considered user experience as important as a company’s products and services. If you consider consumer experiences with brands today, they’re expansive—apps and physical storefronts, personalized interactions, and content syndication. What it takes to create those experiences in a traditional suite is challenging. Marketing and customer success teams want to push the boundaries of what the industry is doing—and there is only so much IT can do to hold the experience together on the back end. 

A composable solution allows marketing to create one version of assets that could be deployed across all channels through an application programming interface (API), meaning that your front-end designers can repurpose the same content across channels simply by tailoring the presentation. The swappable nature of the tools also means that new capabilities can always be added to the stack so that marketers can meet customers with what they want when they want it.

Additionally, traditional architecture forces marketers and IT to work somewhat at cross-purposes. A monolithic architecture might not allow materials to be reused across different platforms, so the marketing team would need to keep track of all channels and make different versions of assets for each. The IT team might then need to do more work to keep track of those assets and deploy them in the proper channels. 

Guess what gets lost in this waiting game? Opportunity. 

Research into retailers’ biggest challenges showed that more than 70 percent currently need more than three weeks to onboard a new vendor to increase their product range. That’s three weeks’ worth of sales they could be missing if they had jumped on the latest pop culture trend.

We are experiencing a sea change in terms of monolithic versus composable architecture, perhaps like the move from mainframes to personal computers many years ago. Gartner even stated that by 2023, organizations with a composable commerce approach will outpace the competition by 80 percent in the speed of feature implementation. More organizations are realizing the power this move can harness for their organizations in reducing risk and maximizing creativity for all.

The post Minimizing Risk in Your MarTech Stack with Composable Architecture appeared first on Best Marketing Automation Software, Tools, Vendors & Solutions.

As part of Solutions Review’s Premium Content Series—a collection of contributed columns written by industry experts in maturing software categories—Jason LaBaw, the Founder and CEO of Social Bee, outlines how generative AI technologies can (and will) impact the travel industry.

First coined by Shakespeare in 1602, the phrase “the world is your oyster” has since become synonymous with adventure and travel. However, many may not realize that, in the original play, the character speaking the line also references a sword he will use to open the oyster to enjoy.  

Cut to 2023, and generative artificial intelligence (AI) is already shaping up to be the sword needed to unlock a new era in travel. Despite launching with initial limitations, such as being less accurate after 2021, the potential of generative AI, such as ChatGPT and Google’s Bard, has received much attention from professionals across industries and the general public.  

Unlike traditional AI, used more for analysis, this latest evolution utilizes large language models (LLMs) and chatbot functions to converse with users and generate new content based on user inputs. This is a game changer for travelers who could soon use such tools to produce detailed itineraries worldwide catered to their unique interests, likes, and dislikes. It’s also an estimated $28 billion-plus opportunity for the travel industry.  

Let’s explore how.  

From AI to Generative AI 

AI allows you to take millions of data sets from all over the world and react quickly to that information. It’s already had a massive impact on the travel industry’s ability to read vast amounts of data, detect patterns, and personalize its product and service offerings.  

Generative AI can already offer many suggestions for activities at your chosen destination. But the current limitation, exemplified in platforms like ChatGPT and Bard, is that it produces a text-based itinerary akin to a blog post that users cannot act from. Instead, users must manually copy, paste, search, and book the activities and accommodations suggested. 

The next evolution of generative AI will facilitate booking flights, accommodations, and excursions with integrations directly from the AI interface. For example, OpenAI, the developers behind ChatGPT, are already working on expanding its web search capabilities with various plug-ins so the chatbot can source real-time information from sites such as Expedia and Instacart.  

In the future, travelers will receive a seamless end-to-end travel planning experience that’s as easy to use as an online booking site. With elevated search functions, generative AI could also use this real-time information on weather patterns, flight prices, and possible travel restrictions to create the most optimized itineraries. Rather than spending countless hours conducting this kind of research, which can intimidate and confuse many prospective travelers, generative AI would be able to gather everything you need to know in a matter of seconds—and book it for you too.  

Consumer-Focused AI 

From personal preferences and current individual itineraries, customer reviews, historical data, news coverage, weather forecasts, and crime reports, the list of data points generative AI could draw from goes on. Travelers’ planning experience is better informed by the millions of more data points that the AI can handle.  

This is how generative AI will help the travel industry become more consumer-focused. While the current generative AI platforms often require some degree of prompt engineering knowledge to extract maximum value, future generative AI platforms will offer a more structured and intuitive user experience. Effectively, this will eliminate the need for users to be experts in LLMs to obtain high-quality results for their queries. Conversely, to a mass-marketing approach, conversational and generative AI will help travelers focus on their interests and create the most unique trip possible.  

A Happy Customer is a Loyal One 

The customer retention rate across industries is, on average, 75 percent. However, the hospitality, travel, and restaurant industry has the lowest customer retention rate at 55 percent. Customer loyalty across the sector has room for improvement, and it’s a valuable business strategy as statistics also show it’s 40-65 percent easier to sell to an existing customer than a new one.  

AI can already remember customer preferences and provide a layer of personalized service offerings based on their previous behavioral and buying patterns. However, generative AI can transform these recommendations into actionable itineraries for buyer conversions. It can also help the industry utilize past purchase history to enhance the customer’s tour, excursion, or experience. 

For travel agents, generative AI represents an opportunity to offer more travel options for their clients that may extend beyond their domain of expertise or regional specialization. This could mean offering tailored activity itineraries and serving customized menus for hotels and restaurants. When people have a good and memorable experience, they’ll want to come back. Maybe you’re a hotel franchise looking to be people’s first choice in a new city, or an independent operator offering a unique trip looking for repeat buyers, client attraction is one thing, but client retention can be the make or break of your business.  

While AI won’t make luxury accommodations accessible to those on a budget, it will arm budget-conscious travelers with itinerary options within their specified budget that are optimized and personalized. Likewise, those with higher budgets will have even more curated options from itineraries tailored to their specific preferences. However, no matter the traveler’s budget, generative AI’s most significant impact is its potential to revolutionize the travel industry by making it easier, more personalized, and more efficient for travelers to plan their trips.

The post How Generative AI Will Impact the Travel Industry appeared first on Best Marketing Automation Software, Tools, Vendors & Solutions.

The editors at Solutions Review have curated this list of the most noteworthy MarTech news from the week of June 30th. This round-up covers announcements and updates from companies like Braze, Salesforce, Wix, and Klaviyo.

Keeping tabs on the most relevant CRM and MarTech news can be time-consuming. As a result, our editorial team aims to summarize the week’s top headlines in the marketing technology landscape. The Solutions Review editors will compile a weekly round-up of vendor product news, mergers and acquisitions, venture capital funding, talent acquisition, and other noteworthy MarTech news. With that in mind, here is some of the top MarTech news from June 30th.

Top MarTech News From the Week of June 30th, 2023

Braze Expands its Artificial Intelligence Capabilities

Braze, a customer engagement platform provider, has announced new updates to its existing artificial intelligence capabilities, now collectively titled Sage AI by Braze. The updated capabilities suite includes an AI-powered recommendation engine for increasing personalization, cross-channel data flows, generative AI features, flexible experimentation tools to optimize customer journeys, and real-time ingestion and execution of customer behavior, preference, and attribute data, enabling the AI to make faster decisions.

Read on for more.

Klaviyo Announces Details on Klaviyo Reviews

Klaviyo—a marketing automation and customer data platform—has launched Klaviyo reviews. This new offering allows Shopify merchants to collect product reviews and the associated customer data and messaging in a single platform. Announced at K:LDN, Klaviyo’s second annual e-commerce summit, Klaviyo reviews can help businesses consolidate their tech stack, personalize data, send messages at the right time, automate review requests, and create unified post-purchase journeys for customers.

Read on for more.

Salesforce Expands its Sales and Service Cloud Platforms with New Generative AI Capabilities

Salesforce has introduced new generative AI capabilities to its Sales Cloud and Service Cloud platforms to help sellers and service teams improve how they work and interact with customers. The new Sales Cloud tools, Sales GPT, embed generative AI technology into the flow of work to help auto-generate customer emails, call summaries, account research, and more. With Service GPT, Service Cloud users can auto-generate service replies, automatically summarize customer interactions into knowledge articles, and equip service agents with the insights they need before arriving at a service location.

Read on for more.

Salesforce Releases a New Solution for Financial Institutions

Salesforce also launched a new solution to help financial institutions use AI, real-time data, and CRM to create automated customer experiences powered by first-party data and generative AI. The new Personalized Financial Engagement solution includes the following tools: Data Cloud for Financial Services, Marketing GPT for Financial Services, MuleSoft Direct for Financial Services Cloud, Marketing Cloud Engagement for Financial Services, and Financial Plans and Goals.

Read on for more.

Salesforce and Deloitte Digital Announce a New Collaboration

Salesforce and Deloitte Digital have announced a new collaboration to equip global businesses with the strategies and accelerators they need to deploy AI for CRM. As part of the partnership, Deloitte Digital will offer its AI services, industry experience, and knowledge of data protection regulations to help businesses implement and scale Salesforce’s AI Cloud suite. The companies will help clients use AI in their CRM solutions to develop personalized customer experiences, protect their data, and maximize productivity.

Read on for more.

Wix Launches Its New SEO Assistant Tool

Wix, a website builder tool, has launched its new SEO Assistant tool. The tool, which includes an extended integration Semrush, provides users with a summary of how each page on their site is doing and gives them detailed, actionable tasks they can fulfill to optimize their pages and content for search engines and visitors. Wix’s SEO Assistant tool is available now to all users for blog pages and will expand to other verticals and pages in the future.

Read on for more.

Expert Insights Section

Watch this space each week as the Solutions Review editors will use it to share new articles from the Expert Insights Series, Contributed Shorts videos, Expert Roundtable videos, event replays, and other curated content to help you gain a forward-thinking analysis and remain on-trend with changing industry expectations. All to meet the demand for what its editors do best: bring industry experts together to publish the web’s leading insights for enterprise technology practitioners.

How Generative AI Can Help SMBs Improve Customer Experiences, by Ramprakash Ramamoorthy of Zoho

As part of Solutions Review’s Premium Content Series, Ramprakash “Ram” Ramamoorthy, the Director of AI Research at Zoho Corporation, explains how generative AI technology can help small-to-medium-sized businesses (SMBs) improve the customer experience, streamline customer service processes, and personalize interactions.

Read on for more.

Are Composable Platforms the Future of Martech?, by Dave O’Flanagan of Sitecore

As part of Solutions Review’s Premium Content Series, Dave O’Flanagan, the Chief Product Officer at Sitecore, talks about the potential composable platforms can bring to the future of marketing technology. In the article, O’Flanagan discusses how composable platforms can help businesses become more agile, personalize customer interactions at scale, and more.

Read on for more.

For consideration in future news round-ups, send your announcements to wjepma@solutionsreview.com.

The post Top MarTech News From the Week of June 30th: Updates from Braze, Salesforce, Wix, and More appeared first on Best Marketing Automation Software, Tools, Vendors & Solutions.

The editors at Solutions Review have compiled this example social media marketing platform RFP template to help your organization select the best enterprise software for its business needs.

Social media marketing is one of the fundamental pillars of a successful marketing strategy, as it can go a long way toward streamlining how your company interacts with its audience, expanding its brand awareness, and creating meaningful connections with prospective and active customers. However, finding the right social media marketing platform is easier said than done, especially considering how many software vendors are in the marketplace.

One way to simplify the process is by using a request for proposal (RFP) template to solicit proposals from potential vendors. In addition to streamlining the vendor selection process, using an RFP template can help you standardize your requirements and evaluation criteria, making comparing proposals from different vendors easier. It can also help ensure you don’t overlook critical requirements or considerations when evaluating solutions.

With that in mind, the Solutions Review editors have compiled an example social media marketing platform RFP template to help you and your team get started.

A Social Media Marketing Platform RFP Template Example

When creating a social media marketing platform RFP, think of it as a short briefing on what your company does, the goals it has for the platform it’s asking about, and the capabilities it needs. The scope of work should also be clearly defined, outlining what the company expects the system to do and including details about any required features or functionalities. By carefully evaluating the RFP and the vendor’s response, you’ll be on your way to finding the best social media marketing platform for your company. Here’s a breakdown of what a marketing automation RFP should include:

1. Introduction and Company Overview: The basis of every social media marketing platform RFP should be a proper overview of your company, its mission, target audience, and current social media presence. Additionally, take some time to describe your current marketing objectives and what you hope to achieve by implementing a new platform into your business.

2. Business Requirements: From there, delve into the specific business requirements and expectations your company has for a social media marketing platform. Consider factors like scalability, user-friendliness, integration with other tools, analytics capabilities, and customer support.

3. Platform Features: List the essential features and functionalities you are seeking in a social media marketing platform. This could include content scheduling, social media automation, analytics, reporting, social listening, influencer management, team collaboration, ad campaign management, and any other requirements unique to your business. Be sure to talk with your marketing team about the feature they prioritize.

4. Platform Integration: Provide prospective vendors with a list of the platforms and tools your organization uses in its marketing efforts. These can include Customer Relationship Management (CRM), Customer Data Platforms (CDPs), email marketing, and more. You should also outline your team’s integration requirements to ensure seamless data flow and a cohesive marketing ecosystem between your existing martech stack and the new platform.

5. Data Security and Privacy: Inquire about the vendor’s data security measures and adherence to privacy regulations by asking for information on data encryption, access controls, data retention policies, and compliance with regulations like GDPR or CCPA.

6. Pricing and Licensing: One of the most important things to ask about is pricing. When connecting with a prospective vendor, ask them for transparent pricing information, including any upfront costs, subscription fees, and additional charges for extra features or user licenses. Inquire about contract terms, renewal options, and potential discounts for long-term commitments.

7. Vendor Experience and Support: Ask for the vendor’s background, including their experience in the industry, client testimonials, and case studies. You can also ask about the level of customer support they typically offer, including response times, available support channels, and training resources that your team can use.

8. Implementation and Onboarding: Seek information on the vendor’s implementation process and estimated timeline. Ask about the availability of onboarding assistance, training programs, and technical support during the transition period, as this is the phase where your team will most appreciate additional support.

9. References: Request a list of current or previous clients who have used the social media marketing platform you’re considering. You can contact these references to gain insights into their experience, satisfaction levels, and any challenges they faced during implementation and usage.

10. Vendor Information and Evaluation Criteria: You should also request each vendor to provide their company background, experience, and relevant case studies, alongside client references and testimonials. Specify the criteria you will use to evaluate proposals, such as functionality, ease of use, scalability, and cost.

NOW READ: Take These Courses to Become a Social Media Marketing Expert

The post A Social Media Marketing Platform RFP Template Example appeared first on Best Marketing Automation Software, Tools, Vendors & Solutions.

As part of Solutions Review’s Premium Content Series—a collection of contributed columns written by industry experts in maturing software categories—Dave O’Flanagan, the Chief Product Officer at Sitecore, talks about the potential composable platforms can bring to the future of marketing technology. 

The days of generic marketing are over. Modern consumers expect personalized experiences and custom content that meets their preferences and needs, and yesterday’s one-size-fits-all marketing platforms are increasingly not up to the task. To meet this challenge, teams have embraced the concept of composable digital experience/martech software. These modular platforms represent an architectural approach that enables businesses to build their e-commerce solutions by combining and integrating best-of-breed components instead of relying on a single monolithic solution, allowing an organization to easily swap in and out individual components without disrupting the entire system.  

It’s a concept that is taking root, with Gartner forecasting that “organizations that have adopted an intelligent composable approach will outpace (the) competition by 80% in the speed of new feature implementation.” This article looks deeper into the benefits of this approach when applied to digital experience software.  

Enabling Agile Adaptivity  

A composable approach to the martech stack enables brands to become more agile and adaptive in their digital strategies. Teams can easily add or replace individual components within the platform to experiment with new technologies, features, or vendors. This allows them to stay ahead of evolving customer expectations, quickly respond to market trends, and optimize their digital experiences.

Another advantage of modular platforms is the ability to experiment with personalization strategies, using A/B testing on campaigns and rapidly iterating to find the most compelling content. This is just one way an integrated stack can streamline workflows for enhanced efficiency. These solutions offer seamless integrations and interoperability, allowing marketers and content creators to work hand-in-hand. Centralized data management and automation also reduce time spent on manual tasks, allowing marketers to focus on strategic initiatives, resulting in improved productivity and faster time-to-market.  

Personalization at Scale  

The demand for unique, personalized content can be overwhelming for marketing teams. By integrating customer data platforms (CDPs) and personalization engines, teams can gather and analyze customer data to gain insight into individual wants and needs to deliver the right content to the right consumer at the right time. Armed with this knowledge, they can curate highly targeted content, such as product recommendations and tailored offers that resonate with consumers, leading to increased engagement, conversion, and satisfaction.  

A modular approach also permits brands to map out and optimize the entire customer journey, from initial touchpoint to post-purchase engagement. When content management systems (CMS) are integrated with marketing automation platforms and analytics, teams can create seamless and consistent experiences for various personas, across multiple channels and devices, depending on the consumer’s preference. A comprehensive approach like this ensures that consumers receive relevant and contextual interactions throughout their journey, building a sense of personal connection and loyalty to a brand.  

Future-Proof Investment   

From an IT perspective, composable platforms allow businesses to optimize their investment in technology by enabling them to select the most cost-effective and efficient components for their needs. Rather than play for an all-in-one solution with features they don’t need, a modular approach enables the inclusion of specialized components that directly address the specific needs of their digital experience teams, allowing for better resource allocation and cost control.  

Additionally, a composable martech stack is easily upgraded. Organizations can keep up with new technological innovations as well as the growing needs of the team. A composable stack enables teams to explore emerging trends and quickly respond to shifts in the market, ensuring that the organization can evolve alongside its customers and keep a competitive advantage.  

Assessing Your Needs  

Composable market platforms offer numerous benefits. However, as mentioned above, one size does not fit all, and there are instances where a composable market platform might not be needed or appropriate. For example, smaller operations with limited resources and relatively straightforward marketing needs might find a modular platform overly complex. 

To determine whether a composable architecture is the right choice for your business, assess your teams’ needs and goals. Once those are understood, determine if a holistic single-vendor digital experience platform can meet those needs or whether they would be better served by a more agile solution built from best-in-breed modules. Either way, it’s crucial to develop a roadmap and align team expectations regarding timing and functionality.  

For most companies, a modular approach will enable them to build a customized martech stack that meets their unique needs, fosters innovation, and promotes the development and delivery of personalized experiences to their customers. By leveraging specialized components and integrating them strategically, brands can experiment, quickly adapt and streamline workflows to develop content and interactions that resonate with customers and strengthens their loyalty.

The post Are Composable Platforms the Future of Martech? appeared first on Best Marketing Automation Software, Tools, Vendors & Solutions.

The editors at Solutions Review compiled a list to spotlight some of the best marketing intelligence tools and platforms to consider based on their reputation, service offerings, and overall user experience.

Data is the backbone of every marketing strategy, but without reliable data, those strategies might not be as successful as they should be. That’s where marketing intelligence solutions can help. Marketing intelligence tools help organizations gather, analyze, and use data from various sources (i.e., customer behaviors, industry trends, competitor behaviors, etc.) to make informed decisions regarding marketing strategies, market trends, and emerging opportunities.

With that in mind, the Solutions Review editors have compiled the following list to spotlight some of the top-rated providers of marketing intelligence tools, platforms, and solutions with the intelligence capabilities companies need to improve a company’s marketing, sales, service, and decision-making strategies.

The Best Marketing Intelligence Tools and Platforms

Adapt.io

Description: Adapt is a global B2B account intelligence solution provider that helps sales reps, marketing leaders, and decision-makers accelerate sales and fill their pipeline with high-quality data on new and existing contacts. The solution can seamlessly integrate with leading CRM solutions. Marketers can use the platform to improve email conversions, build hyper-targeted databases, maintain data hygiene, qualify leads with data, increase traffic by targeting the audience that best matches their ICP, segment leads based on data attributes, run ads on LinkedIn, and more.

Crayon

Description: Crayon is a competitive intelligence platform designed to help mid-market and enterprise businesses gain a complete, real-time picture of what their competitors are doing. The platform can automatically gather, organize, and amplify data from millions of sources to make it easier for users to identify and act on opportunities in their market. Its capabilities include advanced artificial intelligence, machine learning algorithms, customizable reports, sales battlecards, and seamless integrations with leading platforms like Salesforce, HubSpot, Microsoft Teams, Slack, Freshworks, and more.

DealSignal

Description: DealSignal provides accurate, verified B2B data to sales and marketing professionals, helping them maximize efficiency, performance, and results across their strategies. The platform provides users with the tools they need to target the right buyers, personalize outreach, maximize conversion rates, optimize lead scoring, improve data quality, create custom account-based marketing (ABM) campaigns, increase email deliverability, build decision-maker lists, prioritize leads, eliminate manual data entry, streamline prospecting, and more. Users can also integrate the platform with the other tools in their martech stack, including HubSpot, Salesforce, Adobe Marketo, and others.

Demandbase

Description: Demandbase is a go-to-market platform provider for B2B brands. Its platform, Demandbase One, comprises four products—Account-Based Experience (ABX) Cloud, Advertising Cloud, Data Cloud, and Sales Intelligence Cloud—and provides sales and marketing teams with the data tools they need to identify and accelerate opportunities. Its intelligence capabilities include lead-to-account mapping, predictive models, journey stage mapping, engagement heat mapping, automated data cleansing, and data enrichment. Demandbase One pulls data from over 40,000 sources and uses machine learning and AI to validate it.

Meltwater

Description: Meltwater is a global provider of media, social, consumer, and sales intelligence solutions for marketing, sales, executives, PR, and research teams across industries. Its suite includes social media management, media intelligence, media relations, social listening, analytics, influencer marketing, consumer intelligence, data, API integration, and sales intelligence products. Marketers can use Meltwater’s capabilities to capture insights from social media platforms, amplify their messaging, optimize social efforts across channels, grow brand loyalty, prove marketing ROI, and more.

Klue

Description: Klue is an AI-powered “Competitive Enablement” platform created to help marketing teams collect, curate, and deliver actionable competitor insights capable of helping revenue teams win more business. The platform provides companies with the features they need to automate the collection of competitive and marketing intelligence, centralize their data in a single location, develop competitive content that attracts leads, distribute data to relevant teams across the company, measure impact, ensure data security, and integrate with the other tools in their tech stack.

Salesforce

Description:  Salesforce offers one of the most expansive and complete CRM products. The platform includes the company’s sales and marketing applications, most notably the Sales and Marketing Clouds, Service Cloud, Analytics Cloud, App Cloud, and IoT service. With Salesforce’s Marketing Cloud Intelligence offering, companies can optimize spending and improve customer engagement with automated reporting, unified performance data, and AI insights. Features include a library of up-to-date API connectors, automated alerts, visual data models, custom dashboards, built-in integrations, and more.

Semrush

Description: Semrush is an online visibility management SaaS platform and marketing suite for global companies across industries of all sizes. Its suite includes products for content marketing, SEO, competitor research, pay-per-click (PPC) advertising, social media marketing, and more. For companies looking to improve their market research and intelligence capabilities, Semrush provides competitor analysis, traffic analysis, social media tracking, organic search research, paid advertising, competitor PR monitoring, and keyword tracking tools creating content across channels that reaches, engages, and converts the right people.

Similarweb

Description: Similarweb is a website tracking platform that provides companies with a 360-degree view of digital activity across channels, prospects, customers, partners, and competitors. Its solution suite includes products for sales intelligence, digital research, stock intelligence, digital marketing, and shopper intelligence. With its marketing offering, Similarweb can help marketing teams develop, optimize, and manage their competitor analysis, keyword research, pay-per-click (PPC), ad intelligence, and affiliate research efforts, improving their ability to stay ahead of the competition and emerging market trends.

ZoomInfo

Description: ZoomInfo is a go-to-market software, data, intelligence, and revenue operating solution provider that helps B2B sales, marketing, recruiting, and operations professionals drive predictable, accelerated, and sustainable growth for their brands. With its suite of sales, marketing, operations, and talent products, companies have access to features for buyer intent analysis, data enrichment, lead routing, sales automation, cross-channel advertising, conversational intelligence, web form enrichment, deal intelligence, workflow automation, relationship management, and more.

6sense

Description: The 6sense Account Engagement Platform is built to help B2B companies identify opportunities, close sales, and achieve predictable revenue growth. It equips its users with AI-driven predictive models, big data, and machine learning tools they need to create and manage a pipeline. Marketing features include predictive analytics, data enrichment, advertising, workflow orchestration, AI-powered email optimization, pipeline intelligence, and in-depth integrations with 6sense’s proprietary network of B2B publishers, including Bombora, G2, TrustRadius, and PeerSpot.

The post 11 of the Best Marketing Intelligence Tools and Platforms appeared first on Best Marketing Automation Software, Tools, Vendors & Solutions.

The editors at Solutions Review have curated this list of the most noteworthy MarTech news from the week of June 23rd. This round-up covers announcements and updates from companies like Freshworks, Iterable, Zendesk, and more.

Keeping tabs on the most relevant CRM and MarTech news can be time-consuming. As a result, our editorial team aims to summarize the week’s top headlines in the marketing technology landscape. The Solutions Review editors will compile a weekly round-up of vendor product news, mergers and acquisitions, venture capital funding, talent acquisition, and other noteworthy MarTech news. With that in mind, here is some of the top MarTech news from June 23rd.

Top MarTech News From the Week of June 23rd, 2023

Alorica Announces Details on Alorica IQ

Alorica, a global provider of customer experience (CX) solutions, has announced Alorica IQ, a new digital foundry that integrates technology into all its customer interactions and services. Alorica IQ unifies Alorica’s digital solutions, analytics, and consulting services into a new end-to-end offering. It’s designed to help companies transform their brand experience by diving deeper into data around customer preferences, call drivers, and friction points across channels and processes.

Read on for more.

CallMiner Releases a New Real-Time Agent Guidance Product

CallMiner, a conversation intelligence solution provider, has announced RealTime, a new real-time agent guidance product. The new feature combines real-time and post-interaction analytics capabilities to provide organizations with AI-powered tools to improve customer experiences, support agent onboarding, reinforce behaviors with personalized alerts, resolve issues faster, and more. Some of the features and enhancements available with RealTime include Live Insights, Live Listen, and Agent Call for Help, which can empower agents with “next-best-action” guidance, call flow, script adherence support, and up-sell/cross-sell opportunity identification.

Read on for more.

Freshworks Expands its Products with New Generative AI Enhancements

Freshworks has launched several new generative AI enhancements for its product lines to help service, marketing, sales, and IT teams become more efficient with the emerging technology. The new features—Freddy Self-Service, Freddy Copilot, and Freddy Insights—can eliminate busy work by offloading it to bots, offer contextual assistance to users, automate the analysis of daily productivity, generate recommendations that drive business impact, and extract actionable insights from employee work. These three predictive and assistive generative AI capabilities are now available for beta testing.

Read on for more.

Genesys Debuts New Task Management Solutions Tools for the Contact Center

Genesys, a global cloud provider of AI-powered experience orchestration solutions, has announced a new task management solution to help companies automate workflows between contact center employees and other departments. With the new Work Automation and Task Routing tools—available now for the Genesys Cloud CX platform—businesses can create seamless end-to-end customer experiences, bridge the gap between the front and back office, solve customer-related tasks in less time, help employees stay more connected, and streamline post-interaction follow-ups.

Read on for more.

Iterable Details its 2023 Summer Product Release

Iterable, an AI-powered customer communication platform, has unveiled details on its 2023 Summer Product Release. The new release, announced at the company Activate Tour event in London, introduces several new features, including AI-Powered Frequency Management, Global SMS, Flexible Default Locales, and the launch of a new EU Data Center to help EU-based and multi-national brands improve customer trust. These new functionalities will empower users to expand their global reach with SMS marketing, optimize customer engagement, improve the ROI of every message sent, ensure consistent delivery of localized content, and maximize their global return on investment (ROI).

Read on for more.

Salesloft Launches a New Tool Powered by Conductor AI

Salesloft, an AI-powered revenue workflow platform provider, has announced the launch of Rhythm, a new solution powered by Conductor AI, a proprietary, patent-pending AI engine. Rhythm is designed to translate buyer behavior into immediate, impactful seller actions in a prioritized workflow customized to each unique seller. The new tool can seamlessly integrate with other CRMs, sales, and marketing technologies so sellers can save time by staying in one place instead of swiveling from app to app.

Read on for more.

Speedeon Adds Life Event Data to its Customer Intelligence Platform

Speedeon Data—a direct marketing and consumer intelligence solution provider—has added its in-depth life event data to the AudienceMaker platform. By combining the capabilities of a first-party CRM with Speedeon’s third-party consumer marketing data, AudienceMaker can help advertisers maximize the effectiveness of their customer retention and prospect acquisition strategies in a few simple clicks. Lindsey Kaiser, the Chief Product Officer at Speedeon, says, “By putting our life event data into AudienceMaker and keeping it updated around the clock, we’re essentially giving marketers instant access to a pipeline of valuable prospects and current customers who may need their product or service more than ever.”

Read on for more.

Sprinklr Announces the New Features Coming in its Spring Platform Release

Sprinklr, a customer experience management platform for modern enterprises, has launched its spring platform release, which expands its solution suite with over one-hundred new capabilities. The latest release, announced during Customer Contact Week (CCW) in Las Vegas, includes new AI and generative AI-powered capabilities to streamline the process of building, training, implementing, recalibrating, and updating conversational bots with AI models. Other new features can help companies build their Knowledge Base quickly, automatically generate chat responses in multiple languages, and additional CCaaS features to maximize agent productivity.

Read on for more.

Totango Extends its Platform with New In-App Communications Tools

Totango, a composable customer success platform, has announced Totango In-App, a new in-product experience builder. The new solution—advanced by Totango’s acquisition and integration of Lou—will help businesses scale their self-serve user onboarding services, drive product adoptions with in-app announcements, use surveys to capture customer feedback, and more without writing a single line of code. General availability for the new toolset is expected to launch in Fall 2023, but customers can join the closed beta waitlist today.

Read on for more.

Typeface and Salesforce Partner on Generative AI Capabilities

Typeface, a generative AI platform for enterprise content creation, has announced that it has partnered with Salesforce to integrate its brand-personalize generative AI functionalities with Salesforce Marketing GPT. Through the two companies’ partnership, Salesforce and Typeface customers can deliver custom, contextual content across customer journeys, achieve scalable content personalization, boost customer engagement, and increase conversion rates, all powered by generative AI.

Read on for more.

Zendesk Completes its Acquisition of Tymeshift

Zendesk has acquired Tymeshift, an AI-powered modern workforce management (WFM) solution designed to help customers streamline complex customer experience (CX) workload management. Zendesk will combine Tymeshift’s predictive capabilities with its pre-existing AI capabilities to power the “next generation” of AI-assisted CX agent productivity. This will help organizations improve efficiency by automatically managing agent scheduling and making it easier to react to spikes in customer inquiries.

Read on for more.

Expert Insights Section

Watch this space each week as the Solutions Review editors will use it to share new articles from the Expert Insights Series, Contributed Shorts videos, Expert Roundtable videos, event replays, and other curated content to help you gain a forward-thinking analysis and remain on-trend with changing industry expectations. All to meet the demand for what its editors do best: bring industry experts together to publish the web’s leading insights for enterprise technology practitioners.

Your Company’s Outdated Chatbots are Probably Doing More Harm Than Good, by David Greenberg of Conversica

As part of Solutions Review’s Premium Content Series, David Greenberg, the CMO at Conversica, outlines how outdated chatbots can do more harm than good for your business. In the article, Greenberg spotlights how old-school chatbots are often powered by out-of-date technology, the limits that impose around scalability, and why that can negatively affect revenue.

Read on for more.

The Unseen Power of Events: Revolutionizing the Way Marketers Approach Customer’s Journey, by Rodney Hart of RainFocus

As part of Solutions Review’s Premium Content Series, Rodney Hart, the VP of Events at RainFocus, compiled some insights in Q&A form to help marketers see events as a way to change how they approach and manage the customer journey. The discussion touches on subjects like in-person events, how events have changed post-COVID, how event marketers can personalize their events, and what event models work best to develop a strategic marketing strategy.

Read on for more.

For consideration in future news round-ups, send your announcements to wjepma@solutionsreview.com.

The post Top MarTech News From the Week of June 23rd: Updates from Freshworks, Iterable, Zendesk, and More appeared first on Best Marketing Automation Software, Tools, Vendors & Solutions.

As part of Solutions Review’s Premium Content Series—a collection of contributed columns written by industry experts in maturing software categories—David Greenberg, the CMO at Conversica, outlines how outdated chatbots can do more harm than good for your business.

Today’s companies face a problem. Consumers expect more and more of a personal touch in their brand interactions. Yet, the traditional one-rep-to-one-customer approach to growth isn’t scalable. As technology has created the ability to cast a wider net, pulling in more and more leads, it’s not possible to maintain a staff large enough to deliver the expected quality of experience through the entire sales funnel.  

Many business leaders may feel that technology is failing them at a time when, more than ever, they need it to deliver a competitive edge. The traditional, one-way automated engagement methods leveraged over the last two decades to scale are now ineffective for a consumer audience that expects to be treated like a human being and get immediate responses.  

Even technologies that were cutting edge just a few years have not risen to the occasion and have not innovated to support the business. Take, for instance, the usual outdated chatbots you encounter on most websites. These are typically ‘rule-based,’ which means they do not learn or adapt based on new data and function only on the guidelines provided by their initial programming. They were revolutionary two decades ago, but when you put them up against the experience of current Natural Language Processing-powered technology, they feel like using dial-up in a 5G world. Yet, companies persist in entrusting their customer relationships to them.  

To remain competitive, companies must harness the next wave of technologies and move away from their outdated chatbots. Let’s consider four things that make traditional chatbots yesterday’s technology and discuss how the latest advances in Conversational AI can bring businesses back up to the task of pleasing today’s consumers.  

Outdated Chatbots Are Based on Technology That Is Behind the Curve 

Most of us have crossed paths with a chat function on a website that was clearly a chatbot. What gave it away? If you didn’t ask a question, it was pre-programmed to answer; it provided information that may have been vaguely associated with your question but was, for all practical purposes, useless. This may have continued for a few interactions until it was clear that you weren’t getting anywhere, at which point it put you on hold while it connected you with a real person. In a consumer-focused era in which we expect instant results, the chatbot actually delayed your ability to get your needs met. 

Fortunately, this rigid interaction doesn’t represent the current state of Conversational AI. Whereas old models matched specific pre-programmed answers to a narrow set of questions, newer models can adapt on the fly to understand intent, address entirely novel questions, and engage in a level of sophisticated conversation that has previously been limited to human-on-human interaction. Additionally, they can be trained on your company’s band-specific data, giving them an even better understanding of your clientele, products, and industry that allows them to respond with more flexibility and in a more human-like way.  

As a result, this human-like chatbot, more appropriately termed a ‘revenue digital assistant’ because of its ability to contribute directly to the bottom line, can operate as a member of your team. It can carry on personalized, fluid, unscripted 2-way conversations that deliver the best possible experience while guiding the customer down the sales funnel.  

‘Scaling’ Your Team Right Into a Bottleneck 

In theory, the chatbots that support your sales and customer services teams are highly scalable—you can turn as many of them loose on your website as you need to handle the visitor load. In practicality, however, they’ll scale you right into a bottleneck. Once a chatbot encounters a question that falls outside the range of its scripted responses—it siphons the customer off to a human rep. Since this often happens early in the sales process, and because chatbots can do this much faster than a human could, they may send many more frustrated and confused customers to your service and sales reps than they can handle, creating a nightmare bottleneck scenario.  

On the other hand, due to their more sophisticated Conversational AI capabilities, modern platforms can engage in productive conversations with website visitors at all stages of their customer journal. Because they’re assuming a larger portion of the interaction, they offer true scalability by helping more people and putting out more fires while freeing your human employees to spend more high-quality time with customers with more complex needs or who are closer to a sale.   

Chatbots Are Limited to Certain Channels and Use Cases 

Because chatbots are built on rudimentary computing models, they can only perform prescribed functions in particular circumstances. So they are typically limited to a single channel of communication, such as chat, and can only perform well if the website visitor is at the point in their customer journey for which they are optimized. Of course, this isn’t the reality of today’s customer experience, where people often engage with the same company through multiple touchpoints and at different stages in their customer journey.  

If you rely on outdated chatbots, you may be forced to create a strategy designed to work around its shortcomings vs. one designed to give your target audience a great experience. For example, human employees may have to hyper-focus on specific channels or spend undue time and resources on a particular phase of the customer journey simply because it represents a blind spot or limit regarding chatbot capabilities.  

Thanks to the use of much more advanced AI, however, today’s digital assistants can follow engagements with customers and leads through multiple channels, carrying on unscripted conversations that meet them where they are in their journey.   

For example, a customer may initially visit a website in the research phase of their customer journey, where they engage in a conversation with a digital assistant, which provides well-informed answers to their questions and leads them to a contact form in which they volunteer their email. The customer then leaves the website to gather additional information and consider their purchase decision.

After an AI-optimized time interval, the digital assistant may email them with follow-up questions or information. Rather than the scripted, generalized follow-up email that characterizes the automated email campaigns most of us are used to, this email is tailored to the potential customer based on the substance of the initial conversation that took place via website chat. Consequently, they are much more likely to respond to the email, initiating the next phase of the interchange.  

Within a few email exchanges, the digital assistant links to new information the potential customer finds useful. They then return to the website, re-engaging in additional productive two-way conversations with the digital assistant. This process continues, guiding the prospective customer through the sales funnel–to the final purchase and then into the ongoing customer retention phase. 

They Don’t Generate Revenue 

Ultimately, it boils down to the fact that revenue is only generated when you’re building your brand through positive customer interactions and educating your customers on your value proposition quickly while using your resources efficiently enough to maintain a healthy profit margin. The poor experience, lack of scalability, and limited scope of sales models that rely on outdated chatbots can add up to significant revenue loss.   

Fortunately, this doesn’t have to be the case. Updated technology, implemented through the right strategy, can fix this. Using the latest digital assistant platform can create experiences that feel fully human, answering open-ended questions, meeting the customer where they’re at, and giving them what they need to take the next step.  

By controlling and influencing a larger portion of the sales funnel, Conversational AI allows you to strategically engage customers and leads across all digital platforms and at all stages of their customer journey. Instead of creating a queue of frustrated customers for your human employees, they create an excellent customer experience in which questions are promptly and accurately answered, and the right information is offered at the right time.

When human employees are finally brought into the sales process, they work with happier, better-informed sales prospects. In providing this experience, you, in turn, build your brand and your bottom line with happy and satisfied customers.

The post Your Company’s Outdated Chatbots are Probably Doing More Harm Than Good appeared first on Best Marketing Automation Software, Tools, Vendors & Solutions.