Programmatic landscape is likely to see further consolidation: Ramya Parashar, COO, MiQ

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MiQ, a global advertising technology company, known for its better-connected approach to programmatic advertising, the company specializes in connecting data, uncovering insights, and activating them in high-performance campaigns that deliver tangible business outcomes. In a world where making the most of data is increasingly complex, MiQ excels in integrating first-party data, enhancing it with second and third-party sources, and applying data science to extract meaningful insights.

In this exclusive Ag Talk interaction with Adgully, Ramya Parashar, Chief Operating Officer, MiQ, delves into the current state of the programmatic sector in India. She also discusses the specific technologies MiQ has developed to stay ahead in the competitive landscape, how the company is leveraging AI and Generative AI to enhance campaign performance for clients, advancements in CTV advertising, and more.

Could you provide a brief overview of the current state of the programmatic sector in India? What are the key challenges and opportunities for players in this market? How has the pandemic accelerated the adoption of programmatic advertising in India?

Programmatic advertising sector stands as one of the most dynamic and rapidly growing in India and is now an integral part of advertisement techniques. Currently, programmatic is a significant part of the total digital advertising investment, and brands here as well as foreign investors continue to invest more by the year 2023. There are indications that programmatic advertising is being used in the delivery of well targeted and efficient advertising.

AI and machine learning are helping in advancing targeting techniques and offer better ROI for clients. Metrics and analytics are extending their importance as the key means of forming strategies and tactics to identify a target audience, with a focus on the use of first-party data.

As to the challenges, regulations such as GDPR and the India proposed Personal Data Protection Bill become an issue in managing the data and targeting. This is another complex aspect because most entities want to protect their consumer data while at the same time targeting them appropriately.

Some problems concerning the sector include ad fraud, viewability, and the transparency of the supply chain. Preliminary and real time manipulation of ad placements is another critical factor so as to build trust with the advertisers.

As for the numbers of Internet users especially from mid and small cities, there is a wide range of great opportunities. It also means the brands can employ and utilize the new forms of consumers in the digital world. Since India has high mobile usage, mobile programmatic advertising is a big prospect. The use of advertisement positioning and advertising as a promotional technique may also be likely to be more effective on the mobile devices thus leading to the improving of the engagement and conversion rates.

Other areas for improvement with the use of AI as well as machine learning involve targeting precision, better creation of the ads, and the boost of the general performance of the advertising campaign. Employment of these technologies enables one to have a competitive edge in the market. The connection with IT companies, advertising agencies, and brands improves the quality of the offered services and the set of available services.

Impact of the Pandemic has led to acceleration of Digital Adoption. New Channel Development – the COVID-19 pandemic brought a shift in the use of new channels that much forward as buyers were more online.

Businesses still persisted in placing their ads online to reach the target market which was mostly active online. The level of e-commerce transactions rose to the occasion thereby putting pressure on advertisers to spend most of their budgets on digital/ programmatic.

Programmatic was to serve the purpose of advertising and for the Customers’ retargeting within the prospect of online shopping. Increased Demand for Flexibility was seen where advertising agencies wanted more convenient and faster means and ways of advertising that could fit into the exigent circumstances in the market. Real-time bidding and the use of analytics got around this issue nicely by the aid of programmatic advertising.

In other words, as the consumption of the Internet and innovations is growing, the technically oriented sector in India increases relatively quickly. Nevertheless, there are some risks related to data privacy, data quality, and structure of data storage. Still, there are somewhat optimistic expectations for the level of market saturation, the possibilities of mobile advertising, and the use of artificial intelligence. It is additional to say that programmatic advertising has grown into the integral part of companies’ digital advertising tactics, because the pandemic has only contributed to the advancement of technologies.

MiQ is known for its advanced technology and data-driven approach. Could you elaborate on the specific technologies and innovations that MiQ has developed to stay ahead in the competitive programmatic landscape? How is MiQ leveraging AI and Gen AI to enhance campaign performance and deliver better results for clients?

We are known for developing and deploying sophisticated technologies and data products. We stay ahead in the competitive landscape and use AI and Gen AI to enhance campaign performance. We have built and mainstreamed a proper data ecosystem to garner, aggregate and analyse a vast quantity of data from first-party, second-party and third-party sources. Such infrastructure also contributes to MiQ in construction of deeper audience and audiences’ characteristics which are irreplaceable in accurate targeting and interested advertisement processes.

Cross-channel is in-born into MiQ, where a campaign can be smoothly carried across display, video, mobile, CTV and social. The ability to improve quality of the app and the campaign on the fly means we can provide higher CTR, conversions, and ROI by equally fine-tuning bids, creatives, and tags. We prioritise data science initiatives in an attempt to identify improved recipes and approaches to study and predict consumers’ behaviours and specially place the campaign.

For improving the efficiency of the client campaign, we haveother services mainly featuring real-time analytic tools in the form of selected dashboards. These dashboards are created on the ground of the higher degree of the data visualization that would assist the clients to comprehend the tough information and make the right decisions.

With the help of AI, we are able to improve the audience segmentation and targeting since AI has the capability of analysing vast amounts of data to find out numerous patterns and preferences in order to reach its clients. This can be done with much more accuracy; this means that the adverts get to the right people at the right time, hence increasing the chances of engagement and conversion rates.

With Gen AI, we can produce variants of the ad creative and then test the results to find out which creative ads are effective for particular segments, which increases its outcome. Predictive modelling allows us to predict the outcome of a particular campaign thus helping the company to make adjustments where necessary. In this way, MiQ is able to predict which audiences are going to be most likely to convert and thus, can dedicate budgets accordingly, manage bids and adjust targeting strategies in a much more effective manner.

Through the adoption of these technologies and innovations, we are able to obtain excellent feats for our clients in their campaigns. As a fully technology-led organization, we continue to embrace technology and innovation to remain ahead in the programmatic market and assist clients to agree in the ambiguous region of digital advertising.

Connected TV is rapidly gaining traction. How is MiQ positioned in the CTV advertising space? What strategies is MiQ employing to help advertisers effectively reach audiences on CTV through programmatic channels?

We’re well-placed in unfolding the Connected TV advertising (CTV) market by using a data-driven programmatic advertising approach to assist the advertisers in reaching the intended audiences effectively. Pioneering CTV Solutions in creating tailored solutions based on the specifics of CTV ads, knowing the specific intricacies of CTV and its usage, the viewings patterns and diversity of the platforms, we’ve solidified our position as a frontrunner within the sector.

Our proactive approach allows MiQ to place CTV in the perspective of the overall multichannel campaigns, which enables advertisers to adopt CTV as a component of our digital advertising campaigns.

We also leverage our strategic infrastructure to deliver highly targeted viewer audiences to CTV advertisement placements. These include first-party data which is collected directly by advertisers, third-party data that is collected by other parties, and real-time viewing data that is collected by us to ensure that the right audiences are targeted. Regarding cross-device interactive analysis, we have a competitive edge to conduct analytics for CTV, mobile, and desktop devices. It facilitates targeting and campaign optimization since it offers a broader view of the company or brand to the market.

We currently employ highly modelled forms of attribution to measure the impact of CTV on convergent goals and other marketing channels. This enables us to get precise insights regarding the effectiveness of CTV expenditure in the overall marketing communications mix. A detailed analytics and reporting on CTV campaign performance, including metrics like viewability, completion rates, and audience engagement helps our clients make data-driven decisions and optimize their campaigns for better results. We also conduct brand lift studies that assess changes in awareness, consideration, and intent among viewers for clients to understand the qualitative impact of their CTV efforts.

We also partner with leading CTV platforms and publishers to provide access to high-quality, premium inventory. This ensures that advertisers can reach their target audiences in brand-safe, high-engagement environments. By employing advanced targeting, real-time optimization, audience extension, and comprehensive analytics, we help advertisers effectively reach and engage audiences on CTV, ensuring that they maximize the value of their ad spend in this rapidly growing medium.

The industry is undergoing significant changes, such as the cookieless future. How is MiQ preparing for these changes? What are the key trends that you believe will shape the programmatic landscape in the next few years?

At MiQ, we are proactively preparing for these shifts by adopting new technologies, strategies, and approaches. By leveraging First-Party Data we focus on helping clients maximize the use of their first-party data, which is becoming increasingly important as third-party cookies phase out. We create precise audience segments and deliver personalized experiences without relying on third-party cookies.

Building partnerships with data providers and publishers to access high-quality, privacy-compliant data is at our core. These partnerships enable us to continue offering effective targeting and measurement solutions in a cookieless environment. We also use advanced AI and natural language processing (NLP) technologies to deliver relevant ads based on the context of the content users are engaging with, ensuring effective targeting in a cookieless way.

Our Unified ID 2.0 and other deterministic ID frameworks ensure accurate audience targeting and measurement in a cookieless world. These solutions provide a privacy-compliant way to identify and reach users across devices and platforms.

With increasing privacy regulations like GDPR and CCPA, the programmatic landscape is shifting towards more privacy-centric practices. Advertisers and platforms will need to prioritize transparency, consent, and data protection to build trust with consumers. Technologies such as differential privacy, federated learning, and data clean rooms are expected to become more prominent. These technologies allow for data analysis and targeting while minimizing the exposure of personal data. The CTV space is expected to continue its rapid growth, driven by the increasing adoption of streaming services and the shift from traditional TV to digital platforms. CTV has become a central component of omnichannel strategies, offering advertisers access to premium, engaged audiences.

The use of AI for predictive analytics will become more sophisticated, allowing advertisers to anticipate consumer behaviour and trends with greater accuracy. This will enable more proactive campaign strategies and better allocation of ad spend. AI will continue to play a bigger role in creative optimization, generating personalized creatives that resonate with different audience segments. This will lead to higher engagement rates and more effective campaigns.

Overall, the programmatic landscape is likely to see further consolidation, with larger platforms acquiring smaller players to enhance their capabilities and expand their reach. This will lead to more integrated, end-to-end solutions for advertisers.

What measures are being taken to build trust with consumers and ensure transparency in the ad supply chain?

Building trust with consumers by enhancing transparency, security, and compliance is paramount. Programmatic platforms are increasingly aligning their operations with global data privacy regulations such as GDPR and CCPA. These regulations mandate strict guidelines on data collection, consent, and user rights, pushing the industry to adopt more privacy-centric practices. Consent Management Platforms (CMPs) are being widely adopted to ensure that user consent is obtained and managed in compliance with privacy laws. These platforms provide transparency to users about how their data is being used and allow them to control their privacy settings.

Technologies like Differential privacy add noise to data sets to protect individual privacy, while federated learning enables the training of AI models across decentralized data sources without transferring raw data. Advertisers and platforms are also increasingly using data anonymization and encryption techniques to protect user identities. These measures ensure that even if data is intercepted or accessed, it cannot be traced back to individual users.

Supply Path Optimization, SPO techniques have been employed to streamline the ad supply chain and eliminate inefficient or fraudulent intermediaries. By optimizing the path from advertiser to publisher, we reduce the risk of ad fraud and ensure that ad spend is directed towards legitimate inventory.

Apart from these, the IAB’s Open Measurement Software Development Kit, SDK standardizes how viewability and ad verification metrics are measured across different platforms and devices. This standardization enhances transparency and allows advertisers to trust the reported metrics. Tools that assess the context in which ads appear are becoming more advanced, allowing advertisers to ensure that their ads are placed in environments that align with their brand values. This contextual understanding helps avoid placements in harmful or inappropriate content.

Building direct relationships with consumers through first-party data collection allows advertisers to create personalized experiences without relying on third-party data. These direct relationships are more transparent and can enhance trust.