Kernel Metadata Declaration — on demand
ISO 26324 asks a DOI Registration Agency to produce a Kernel Metadata Declaration for every DOI it issues. Give any DOI: its public record becomes a record in the Smart Scholars DOI Metadata Format 1.0, checked against every rule, and declared as the Kernel XML.
✓ Meets every rule of the format
The record below is complete and every controlled value is a DOI Attribute Value Set 2.3 spelling. The Declaration on the right follows DOIMetadataKernel.xsd element by element.
What the DOI identifies
Leveraging AI-Driven Sales Intelligence to Revolutionize CRM Forecasting with Predictive Analytics
10.46243/jst.2025.v10.i05.pp29-37 · JournalArticle — an article in a journal · Digital · Visual · Language
Published 2025-05-16
Part of Journal of Science & Technology · ISSN 2456-5660 · vol. 10 · no. 5 · pp. 29–37
Principal agents
- GIRISH KOTTE (author → Author)
- Longman Publishers (publisher → Publisher)
Also in the record, outside the Kernel: the abstract, the licence, 2 links, 21 references. Source: Crossref (member 25296), registered 2025-06-05, last deposited 2026-09-07.
System metadata — ISO 26324:2025, Annex B · DOI Handbook 10.1
Each element by the standard's name and the Handbook's (in grey), read off the record.
| DOI Name DOI name | 10.46243/jst.2025.v10.i05.pp29-37 |
| Referent Type referentType | Creation |
| Referent Sub-Type referentSubType | JournalArticle — an article in a journal |
| Referent Name(s) referentName(s) | Leveraging AI-Driven Sales Intelligence to Revolutionize CRM Forecasting with Predictive Analytics (PrincipalTitle) |
| Basic Metadata basicMetadata | author: GIRISH KOTTE publisher: Longman Publishers published: 2025-05-16 part of: Journal of Science & Technology · ISSN 2456-5660 · vol. 10 · no. 5 · pp. 29–37 form: Digital · Visual · Language |
| Referent Identifier(s) alternateIdentifier(s) | none besides the DOI |
| Registration Authority registrationAuthorityCode | Crossref — issued by Crossref (member 25296); held here as a copy |
| Created Date issueDate | 2025-06-05 |
| relatedIdentifiers | none needed — the descriptive metadata is in this record |
The record
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"doi": "10.46243/jst.2025.v10.i05.pp29-37",
"referent": "Creation",
"type": "JournalArticle",
"structural_type": "Digital",
"modes": [
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"characters": [
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"titles": [
{
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"type": "PrincipalTitle"
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"identifiers": [
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"return_type": "text/html",
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{
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"abstract": {
"value": "The focus of this research is to study the results of the use of AI enabled sales intelligence and predictive analytics onCRM systems. The combination of AI and CRM makes CM forecasting more accurate and productive throughprediction of future trends based on customer data analysis. Predictive analytics provides data-driven insights that helpoptimize sales tactics and decision-making processes. Customer interaction and personalization in CRM systemsbecome more open to strong connections in the time of AI is included. Updates are available continuously and dataruns into the AI models in real time. The results confirm the great enhancement of CRM performance and companyoutcomes provided by AI. The importance of future research is in further refining methodology to create CRM basedon the needs of specific industries for optimal results."
},
"license": {
"url": "https://creativecommons.org/licenses/by/4.0",
"start": "2025-05-16",
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"references": [
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"unstructured": "Venkataramanan, S., Sadhu, A.K.R., Gudala, L. and Reddy, A.K., 2024. Leveraging artificial intelligence for enhanced sales forecasting accuracy: a review of AI-driven techniques and practical applications in customer relationship management systems. Aust. J. Mach. Learn. Res. Appl, 4, pp.267-287"
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"unstructured": "Iqbal, T. and Khan, M.N., 2021. The Impact of Artificial Intelligence (AI) on CRM and Role of Marketing Managers"
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"doi": "10.1016/j.iot.2022.100514",
"unstructured": "Gill, S.S., Xu, M., Ottaviani, C., Patros, P., Bahsoon, R., Shaghaghi, A., Golec, M., Stankovski, V., Wu, H., Abraham, A. and Singh, M., 2022. AI for next generation computing: Emerging trends and future directions. Internet of Things, 19, p.100514"
},
{
"key": "ref4",
"doi": "10.1007/s10799-023-00388-w",
"unstructured": "Wu, M., Andreev, P. and Benyoucef, M., 2024. The state of lead scoring models and their impact on sales performance. Information Technology and Management, 25(1), pp.69-98"
},
{
"key": "ref5",
"doi": "10.56781/ijsret.2024.4.1.0021",
"unstructured": "Adeniran, I.A., Efunniyi, C.P., Osundare, O.S. and Abhulimen, A.O., 2024. Enhancing security and risk management with predictive analytics: A proactive approach. International Journal of Management & Entrepreneurship Research, 6(8)"
},
{
"key": "ref6",
"doi": "10.30574/ijsra.2021.3.1.0111",
"unstructured": "Egbuhuzor, N.S., Ajayi, A.J., Akhigbe, E.E., Agbede, O.O., Ewim, C.P.M. and Ajiga, D.I., 2021. Cloud-based CRM systems: Revolutionizing customer engagement in the financial sector with artificial intelligence. International Journal of Science and Research Archive, 3(1), pp.215-"
},
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"doi": "10.2139/ssrn.5283654",
"unstructured": "Kishen, R., Upadhyay, S., Jaimon, F., Suresh, S., GIRISH KOTTE: Leveraging AI-Driven Sales Intelligence to Revolutionize CRM Forecasting with Predictive Analytics"
},
{
"key": "ref8",
"doi": "10.53430/ijeru.2024.7.1.0032",
"unstructured": "Okeleke, P.A., Ajiga, D., Folorunsho, S.O. and Ezeigweneme, C., 2024. Predictive analytics for market trends using AI: A study in consumer behavior. International Journal of Engineering Research Updates, 7(1), pp.36-49"
},
{
"key": "ref9",
"doi": "10.1007/s11831-021-09700-9",
"unstructured": "Sharma, A., Mukhopadhyay, T., Rangappa, S.M., Siengchin, S. and Kushvaha, V., 2022. Advances in computational intelligence of polymer composite materials: machine learning assisted modeling, analysis and design. Archives of Computational Methods in Engineering, 29(5), pp.3341-3385"
},
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"key": "ref10",
"doi": "10.55248/gengpi.5.1024.2911",
"unstructured": "Adeyeye, O.J., Akanbi, I., Emeteveke, I. and Emehin, O., 2024. Leveraging secured AI-driven data analytics for cybersecurity: Safeguarding information and enhancing threat detection. International Journal of Research and Publication and Reviews, 5(10), pp.3208-3223"
},
{
"key": "ref11",
"doi": "10.1007/s11747-020-00749-9",
"unstructured": "Huang, M.H. and Rust, R.T., 2021. A strategic framework for artificial intelligence in marketing. Journal of the academy of marketing science, 49, pp.30-50"
},
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"unstructured": "Venkataramanan, S., Sadhu, A.K.R., Gudala, L. and Reddy, A.K., 2024. Leveraging artificial intelligence for enhanced sales forecasting accuracy: a review of AI-driven techniques and practical applications in customer relationship management systems. Aust. J. Mach. Learn. Res. Appl, 4, pp.267-287"
},
{
"key": "ref13",
"doi": "10.1080/08853134.2023.2183214",
"unstructured": "Elhajjar, S., Yacoub, L. and Ouaida, F., 2024. The present and future of the B2B sales profession. Journal of Personal Selling & Sales Management, 44(2), pp.128-141"
},
{
"key": "ref14",
"doi": "10.1038/s41746-022-00611-y",
"unstructured": "Feng, J., Phillips, R.V., Malenica, I., Bishara, A., Hubbard, A.E., Celi, L.A. and Pirracchio, R., 2022. Clinical artificial intelligence quality improvement: towards continual monitoring and updating of AI algorithms in healthcare. NPJ digital medicine, 5(1), p.66. Kozlova, N., Bozhuk, S., Mottaeva, A.B., Barykin, S.Y. and Matchinov, V.A., 2021. Prospects for artificial intelligence implementation to design personalized customer engagement strategies. Pt. 2 J. Legal Ethical & Regul. Isses, 24, p.1"
},
{
"key": "ref15",
"doi": "10.1007/s00778-022-00775-9",
"unstructured": "Whang, S.E., Roh, Y., Song, H. and Lee, J.G., 2023. Data collection and quality challenges in deep learning: A data-centric ai perspective. The VLDB Journal, 32(4), pp.791-813"
},
{
"key": "ref16",
"doi": "10.60087/jaigs.v3i1.118",
"unstructured": "Smith, J.D., 2024. The Impact of Technology on Sales Performance in B2B Companies. Journal of Artificial Intelligence General science (JAIGS) ISSN: 3006-4023, 3(1), pp.246-261"
},
{
"key": "ref17",
"doi": "10.31449/inf.v46i5.3853",
"unstructured": "Dahr, J.M., Hamoud, A.K., Najm, I.A. and Ahmed, M.I., 2022. Implementing sales decision support system using data mart based on olap, kpi, and data mining approaches. Journal of engineering science and technology, 17(1), pp.275-293"
},
{
"key": "ref18",
"unstructured": "Motevalli, S.H. and Razavi, H., 2024. Enhancing Customer Experience and Business Intelligence: The Role of AI-Driven Smart CRM in Modern Enterprises. Journal of Business and Future Economy, 1(2), pp.1-8"
},
{
"key": "ref19",
"doi": "10.1007/s11135-020-01072-9",
"unstructured": "Casula, M., Rangarajan, N. and Shields, P., 2021. The potential of working hypotheses for deductive exploratory research. Quality & Quantity, 55(5), pp.1703-1725"
},
{
"key": "ref20",
"doi": "10.1177/15586898221126816",
"unstructured": "Proudfoot, K., 2023. Inductive/deductive hybrid thematic analysis in mixed methods research. Journal of mixed methods research, 17(3), pp.308-326"
},
{
"key": "ref21",
"doi": "10.1038/s41746-022-00611-y",
"unstructured": "Feng, J., Phillips, R.V., Malenica, I., Bishara, A., Hubbard, A.E., Celi, L.A. and Pirracchio, R., 2022. Clinical artificial intelligence quality improvement: towards continual monitoring and updating of AI algorithms in healthcare. NPJ digital medicine, 5(1), p.66"
}
],
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"updated": "2026-09-07",
"issue_number": 1,
"source": "crossref-api",
"source_agency": "Crossref (member 25296)"
}
}The Kernel Metadata Declaration
DOIMetadataKernel.xsd · namespace http://www.doi.org/2010/DOISchema · Attribute Value Sets 2.3 · draft — the agency's DOI name is filled in on accreditation
<?xml version="1.0" encoding="UTF-8"?>
<!-- DRAFT declaration: Smart Scholars is not yet a DOI Registration Agency. registrationAgencyDoiName is a marker (10.0/ is no RA's prefix) and is filled in on accreditation. -->
<kernelMetadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.doi.org/2010/DOISchema https://www.doi.org/doi_schemas/DOIMetadataKernel.xsd" xmlns="http://www.doi.org/2010/DOISchema">
<referentDoiName>10.46243/jst.2025.v10.i05.pp29-37</referentDoiName>
<primaryReferentType>Creation</primaryReferentType>
<registrationAgencyDoiName>10.0/smart-scholars-draft</registrationAgencyDoiName>
<issueDate>2026-10-04</issueDate>
<issueNumber>1</issueNumber>
<referentCreation>
<name>
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<type>DOI</type>
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<identifier>
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<type>URI</type>
</identifier>
<identifier>
<uri>https://jst.org.in/index.php/pub/article/download/1267/988</uri>
<type>URI</type>
</identifier>
<structuralType>Digital</structuralType>
<mode>Visual</mode>
<character>Language</character>
<type>JournalArticle</type>
<principalAgent>
<name>
<value>GIRISH KOTTE</value>
<type>PrincipalName</type>
</name>
<role>Author</role>
</principalAgent>
<principalAgent>
<name>
<value>Longman Publishers</value>
<type>PrincipalName</type>
</name>
<role>Publisher</role>
</principalAgent>
<linkedCreation>
<name>
<value>Journal of Science & Technology</value>
<type>PrincipalTitle</type>
</name>
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